Search Results

Search found 7216 results on 289 pages for 'low cost'.

Page 38/289 | < Previous Page | 34 35 36 37 38 39 40 41 42 43 44 45  | Next Page >

  • What’s Your Tax Strategy? Automate the Tax Transfer Pricing Process!

    - by tobyehatch
    Does your business operate in multiple countries? Well, whether you like it or not, many local and international tax authorities inspect your tax strategy.  Legal, effective tax planning is perceived as a “moral” issue. CEOs are being asked to testify on their process of tax transfer pricing between multinational legal entities.  Marc Seewald, Senior Director of Product Management for EPM Applications specializing in all tax subjects and Product Manager for Oracle Hyperion Tax Provisioning, and Bart Stoehr, Senior Director of Product Strategy for Oracle Hyperion Profitability and Cost Management joined me for a discussion/podcast on this interesting subject.  So what exactly is “tax transfer pricing”? Marc defined it this way. “Tax transfer pricing is a profit allocation methodology required to be used by multinational corporations. Specifically, the ultimate goal of the transfer pricing is to ensure that the global multinational pays their fair share of income tax in each of their local markets. Specifically, it prevents companies from unfairly moving profit from ‘high tax’ countries to ‘low tax’ countries.” According to Marc, in today’s global economy, profitability can be significantly impacted by goods and services exchanged between the related divisions within a single multinational company.  To ensure that these cost allocations are done fairly, there are rules that govern the process. These rules ensure that intercompany allocations fairly represent the actual nature of the businesses activity- as if two divisions were unrelated - and provide a clear audit trail of how the costs have been allocated to prove that allocations fall within reasonable ranges.  What are the repercussions of improper tax transfer pricing? How important is it? Tax transfer pricing allocations can materially impact the amount of overall corporate income taxes paid by a company worldwide, in some cases by hundreds of millions of dollars!  Since so much tax revenue is at stake, revenue agencies like the IRS, and international regulatory bodies like the Organization for Economic Cooperation and Development (OECD) are pushing to reform and clarify reporting for tax transfer pricing. Most recently the OECD announced an “Action Plan for Base Erosion and Profit Shifting”. As Marc explained, the times are changing and companies need to be responsive to this issue. “It feels like every other week there is another company being accused of avoiding taxes,” said Marc. Most recently, Caterpillar was accused of avoiding billions of dollars in taxes. In the last couple of years, Apple, GE, Ikea, and Starbucks, have all been accused of tax avoidance. It’s imperative that companies like these have a clear and auditable tax transfer process that enables them to justify tax transfer pricing allocations and avoid steep penalties and bad publicity. Transparency and efficiency are what is needed when it comes to the tax transfer pricing process. Bart explained that tax transfer pricing is driving a deeper inspection of profit recognition specifically focused on the tax element of profit.  However, allocations needed to support tax profitability are nearly identical in process to allocations taking place in other parts of the finance organization. For example, the methods and processes necessary to arrive at tax profitability by legal entity are no different than those used to arrive at fully loaded profitability for a product line. In fact, there is a great opportunity for alignment across these two different functions.So it seems that tax transfer pricing should be reflected in profitability in general. Bart agreed and told us more about some of the critical sub-processes of an overall tax transfer pricing process within the Oracle solution for tax transfer pricing.  “First, there is a ton of data preparation, enrichment and pre-allocation data analysis that is managed in the Oracle Hyperion solution. This serves as the “data staging” to the next, critical sub-processes.  From here, we leverage the Oracle EPM platform’s ability to re-use dimensions and legal entity driver data and financial data with Oracle Hyperion Profitability and Cost Management (HPCM).  Within HPCM, we manage the driver data, define the legal entity to legal entity allocation rules (like cost plus), and have the option to test out multiple, simultaneous tax transfer pricing what-if scenarios.  Once processed, a tax expert can evaluate the effectiveness of any one scenario result versus another via a variance analysis configured with HPCM’s pre-packaged reporting capability known as Oracle Hyperion SmartView for Office.”   Further, Bart explained that the ability to visibly demonstrate how a cost or revenue has been allocated is really helpful and auditable.  “HPCM’s Traceability Maps are that visual representation of all allocation flows that have been executed and is the tax transfer analyst’s best friend in maintaining clear documentation for tax transfer pricing audits. Simply click and drill as you inspect the chain of allocation definitions and results. Once final, the post-allocated tax data can be compared to the GL to create invoices and journal entries for posting to your GL system of choice.  Of course, there is a framework for overall governance of the journal entries, allocation percentages, and reporting to include necessary approvals.” Lastly, Marc explained that the key value in using the Oracle Hyperion solution for tax transfer pricing is that it keeps everything in alignment in one single place. Specifically, Oracle Hyperion effectively becomes the single book of record for the GAAP, management, and the tax set of books. There are many benefits to having one source of the truth. These include EFFICIENCY, CONTROLS and TRANSPARENCY.So, what’s your tax strategy? Why not automate the tax transfer pricing process!To listen to the entire podcast, click here.To learn more about Oracle Hyperion Profitability and Cost Management (HPCM), click here.

    Read the article

  • How do I do TDD on embedded devices?

    - by Darth
    I'm not new to programming and I've even worked with some low level C and ASM on AVR, but I really can't get my head around a larger-scale embedded C project. Being degenerated by the Ruby's philosophy of TDD/BDD, I'm unable to understand how people write and test code like this. I'm not saying it's a bad code, I just don't understand how this can work. I wanted to get more into some low level programming, but I really have no idea how to approach this, since it looks like a completely different mindset that I'm used to. I don't have trouble understanding pointer arithmetics, or how allocating memory works, but when I see how complex C/C++ code looks compared to Ruby, it just seems impossibly hard. Since I already ordered myself an Arduino board, I'd love to get more into some low level C and really understand how to do things properly, but it seems like none of the rules of high level languages apply. Is it even possible to do TDD on embedded devices or when developing drivers or things like custom bootloader, etc.?

    Read the article

  • HPCM 11.1.2.2.x - How to find data in an HPCM Standard Costing database

    - by Jane Story
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} When working with a Hyperion Profitability and Cost Management (HPCM) Standard Costing application, there can often be a requirement to check data or allocated results using reporting tools e.g Smartview. To do this, you are retrieving data directly from the Essbase databases related to your HPCM model. For information, running reports is covered in Chapter 9 of the HPCM User documentation. The aim of this blog is to provide a quick guide to finding this data for reporting in the HPCM generated Essbase database in v11.1.2.2.x of HPCM. In order to retrieve data from an HPCM generated Essbase database, it is important to understand each of the following dimensions in the Essbase database and where data is located within them: Measures dimension – identifies Measures AllocationType dimension – identifies Direct Allocation Data or Genealogy Allocation data Point Of View (POV) dimensions – there must be at least one, maximum of four. Business dimensions: Stage Business dimensions – these will be identified by the Stage prefix. Intra-Stage dimension – these will be identified by the _Intra suffix. Essbase outlines and reporting is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s02.html For additional details on reporting measures, please review this section of the documentation:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/apas03.html Reporting requirements in HPCM quite often start with identifying non balanced items in the Stage Balancing report. The following documentation link provides help with identifying some of the items within the Stage Balancing report:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/generatestagebalancing.html The following are some types of data upon which you may want to report: Stage Data: Direct Input Assigned Input Data Assigned Output Data Idle Cost/Revenue Unassigned Cost/Revenue Over Driven Cost/Revenue Direct Allocation Data Genealogy Allocation Data Stage Data Stage Data consists of: Direct Input i.e. input data, the starting point of your allocation e.g. in Stage 1 Assigned Input Data i.e. the cost/revenue received from a prior stage (i.e. stage 2 and higher). Assigned Output Data i.e. for each stage, the data that will be assigned forward is assigned post stage data. Reporting on this data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s03.html Dimension Selection Measures Direct Input: CostInput RevenueInput Assigned Input (from previous stages): CostReceivedPriorStage RevenueReceivedPriorStage Assigned Output (to subsequent stages): CostAssignedPostStage RevenueAssignedPostStage AllocationType DirectAllocation POV One member from each POV dimension Stage Business Dimensions Any members for the stage business dimensions for the stage you wish to see the Stage data for. All other Dimensions NoMember Idle/Unassigned/OverDriven To view Idle, Unassigned or Overdriven Costs/Revenue, first select which stage for which you want to view this data. If multiple Stages have unassigned/idle, resolve the earliest first and re-run the calculation as differences in early stages will create unassigned/idle in later stages. Dimension Selection Measures Idle: IdleCost IdleRevenue Unassigned: UnAssignedCost UnAssignedRevenue Overdriven: OverDrivenCost OverDrivenRevenue AllocationType DirectAllocation POV One member from each POV dimension Dimensions in the Stage with Unassigned/ Idle/OverDriven Cost All the Stage Business dimensions in the Stage with Unassigned/Idle/Overdriven. Zoom in on each dimension to find the individual members to find which members have Unassigned/Idle/OverDriven data. All other Dimensions NoMember Direct Allocation Data Direct allocation data shows the data received by a destination intersection from a source intersection where a direct assignment(s) exists. Reporting on direct allocation data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s04.html You would select the following to report direct allocation data Dimension Selection Measures CostReceivedPriorStage AllocationType DirectAllocation POV One member from each POV dimension Stage Business Dimensions Any members for the SOURCE stage business dimensions and the DESTINATION stage business dimensions for the direct allocations for the stage you wish to report on. All other Dimensions NoMember Genealogy Allocation Data Genealogy allocation data shows the indirect data relationships between stages. Genealogy calculations run in the HPCM Reporting database only. Reporting on genealogy data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s05.html Dimension Selection Measures CostReceivedPriorStage AllocationType GenealogyAllocation (IndirectAllocation in 11.1.2.1 and prior versions) POV One member from each POV dimension Stage Business Dimensions Any stage business dimension members from the STARTING stage in Genealogy Any stage business dimension members from the INTERMEDIATE stage(s) in Genealogy Any stage business dimension members from the ENDING stage in Genealogy All other Dimensions NoMember Notes If you still don’t see data after checking the above, please check the following Check the calculation has been run. Here are couple of indicators that might help them with that. Note the size of essbase cube before and after calculations ensure that a calculation was run against the database you are examing. Export the essbase data to a text file to confirm that some data exists. Examine the date and time on task area to see when, if any, calculations were run and what choices were used (e.g. Genealogy choices) If data does not exist in places where they are expecting, it could be that No calculations/genealogy were run No calculations were successfully run The model/data at feeder location were either absent or incompatible, resulting in no allocation e.g no driver data. Smartview Invocation from HPCM From version 11.1.2.2.350 of HPCM (this version will be GA shortly), it is possible to directly invoke Smartview from HPCM. There is guided navigation before the Smartview invocation and it is then possible to see the selected value(s) in SmartView. Click to Download HPCM 11.1.2.2.x - How to find data in an HPCM Standard Costing database (Right click or option-click the link and choose "Save As..." to download this pdf file)

    Read the article

  • Buzzword for "performance-aware" software development

    - by errantlinguist
    There seems to be an overabundance of buzzwords for software development styles and methodologies: Agile development, extreme programming, test-driven development, etc... well, is there any sort of buzzword for "performance-aware" development? By "performance awareness", I don't necessarily mean low-latency or low-level programming, although the former would logically fall under the blanket term I'm looking for. I mean development in which resources are recognised to be finite and so there is a general emphasis on low computational complexity, good resource management, etc. If I was to be snarky, I would say "good programming", but that doesn't seem to get the message across so well...

    Read the article

  • Video capture Performance

    - by volting
    I have noticed high CPU utilization in a number of applications (except mplayer) which read from the embedded webcam on my laptop. Bizarrely CPU utilization varies proportionately to the level of illumination present. I know that that high CPU usage has nothing to do with rendering the video, as I have written a simple app using the OpenCV library to simply grab frames from the webcam, and cpu usage is still high. I think that mplayer might be using my GPU (and the other apps aren't), but since its not an issue with rendering, I dont think this explains anything. Cheese Low light --- ~12% CPU Bright Light ---- ~63% CPU Camorama Low light --- ~7% CPU Bright Light ---- ~30% CPU Opencv C++ library, (display in a single highgui window) Low light --- ~13% CPU Bright Light ---- ~40% CPU (same test on windows 7, 4-9%) Mplayer No problem, 1-2% regardless of light levels Note: If all I want't to do is capture a feed from my webcam I would use mplayer and forget about it, but I'm developing an application which uses the OpenCV to capture a video feed among other things, performance is important.

    Read the article

  • Application qos involving priority and bandwidth

    - by Steve Peng
    Our manager wants us to do applicaiton qos which is quite different from the well-known system qos. We have many services of three types, they have priorites, the manager wants to suspend low priority services requests when there are not enough bandwidth for high priority services. But if the high priority services requests decrease, the bandwidth for low priority services should increase and low priority service requests are allowed again. There should be an algorithm involving priority and bandwidth. I don't know how to design the algorithm, is there any example on the internet? Somebody can give suggestion? Thanks. UPDATE All these services are within a same process. We are setting the maximum bandwidth for the three types of services via ports of services via TC (TC is the linux qos tool whose name means traffic control).

    Read the article

  • Developing Schema Compare for Oracle (Part 6): 9i Query Performance

    - by Simon Cooper
    All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

    Read the article

  • What exactly does "keyword" mean in the context of AdSense CPC?

    - by deltanovember
    I have read in a lot of places that CPC depends on the value of "keywords". However I don't understand what this means. I will set forward some scenarios. Suppose I run a blog about knitting and this is a low paying niche. However I suddenly write five frontpage blog posts about forex trading and insurance. When people click on the frontpage ads, would I be getting paid for the low CPC knitting content or for the high paying forex content? Suppose somebody finds my webpage by searching for knitting. However the actual content of the landing page is filled with high paying keywords. Is the CPC for this page determined by the low paying search or the high paying content?

    Read the article

  • Answers to Conference Revenue Tweet Questions

    - by D'Arcy Lussier
    Originally posted on: http://geekswithblogs.net/dlussier/archive/2014/05/27/156612.aspxI tweeted this the other day… …and I had some people tweet back questioning/asking about the profit number. So here’s how I came to that figure. Total Revenue Let’s talk total revenue first. This conference has a huge list of companies/organizations paying some amount for sponsorship. Platinum ($1500) x 5 = $7500 Gold ($1000) x 3 = $3000 Silver ($500) x 9 = $4500 Bronze ($250) x 13 = $3250 There’s also a title sponsor level but there’s no mention of how much that is…more than $1500 though, so let’s just say $2500. Total Sponsorship Revenue: $20750.00 For registrations, this conference is claiming over 300 attendees. We’ll just calculate at 300 and the discounted “member rate” – $249. Total Registration Revenue: $74700.00 Booth space is also sold for a vendor area, but let’s just leave that out of the calculation. Total Event Revenue: $95450.00 Now that we know how much money we’re playing with, let’s knock out the costs for the event. Total Costs Hard Costs Audio/Visual Services $2000 Conference Rooms (4 Breakouts + Plenary) $2500 Insurance $700 Printing/Signage $1500 Travel/Hotel Rooms $2000 Keynotes $2000 So let’s talk about these hard costs first. First you may be asking about the Audio Visual. Yes those services can be that high, actually higher. But since there’s an A/V company touted as the official A/V provider, I gotta think there’s some discount for being branded as such. Conference rooms are actually an inflated amount of $500 per. Venues make money on the food they sell at events, not on room rentals. The more food, the cheaper the rooms tend to be offered at. Still, for the sake of argument, let’s set the rooms at $500 each knowing that they could be lower. For travel and hotel rooms…it appears that most of the speakers at this conference are local, meaning there’s no travel or hotel cost. But a few of them I wasn’t too sure…so let’s factor in enough to cover two outside speakers (airfare and hotel). There are two keynotes for this event and depending on the event those may be paid gigs. I’m not sure if they are or not, but considering the closing one is a comedian I’m going to add some funds here for that just in case. Total Hard Costs: $10700 Now that the hard costs are out of the way, let’s talk about the food costs. Food Costs The conference is providing a continental breakfast (YEEEESH!), some level of luncheon, and I have to assume coffee breaks in between. Let’s look at those costs. Continental Breakfast $12 per person Lunch Buffet $18 per person Coffee Breaks (2) $6 per person (or $3 a cup) Snacks (2) $10 per person (or $5 each) Note that the lunch buffet assumes a *good* lunch buffet – two entrees, starch, vegetable, salads, and bread. Not sure if there’ll be snacks during coffee breaks but let’s assume so. Total Food Cost Per Person: $46 Food Cost: $14950 Gratuity: $2691 Total Food Cost: $17641 Total food cost is based on the $46 per person cost x 325. 300 for attendance, 12 for speakers, extra 13 for volunteers/organizers. Gratuity is 18%. Grand Totals So let’s sum things up here. Total Costs Hard Costs: $10700.00 Food Costs: $17641.00 Total:          $28341.00 Taxes:         $3685.00 Grand Total  $32026.00 Total Revenue Sponsorship  $20750 Registration   $74700 Grand Total   $95450.00 Total Profit $63424.00 Now what if the registration numbers were lower and they only got 100 people to show up. In that scenario there’d still be a profit of just under $26000. Closing Comments A couple of things to note: - I haven’t factored in anything for prizes. Not sure if any will be given out - We didn’t add in the booth space revenue - We’re assuming speakers aren’t getting paid, but even if they were at the high end its $12000 ($1000 per session), which is probably an inflated number for local speakers. - Note that all registrations were set to the “member” discounted price. The non-member registration price is higher. There is also an option for those that just want to show up for the opening keynote. There you have it! Let me know if you have any questions. D

    Read the article

  • Need a CDN with SSL

    - by Till
    We currently use Edgecast through Speedyrails. Back when I did my research they were both fast and very cost-effective. I haven't looked in a while, but now we need SSL on our assets as well. I reached out to our current provider and they want a setup fee and something like 260 USD per host per month (we use multiple hosts currently). I looked at AWS Cloudfront and it seems the most cost affective way to get SSL, but it's not a custom domain then (e.g. cdn.example.org), which I could live with. Has any else researched this lately and has any providers to get in touch with - can be resellers or direct buys. I'm not looking for a bargain, I just want to get an idea what these things cost. Edit, 2012-08-23: Must have is custom origin. E.g. I don't want to manually upload files somewhere else. Edgecast and Cloudfront both support this.

    Read the article

  • Announcing StorageTek VSM 6

    - by uwes
    On 23rd of October Oracle announced the 6th generation StorageTek Virtual Storage Manager system (StorageTek VSM 6). StorageTek VSM 6 provides customers simple, flexible and mainframe class reliability all while reducing a customer’s total cost of ownership: Simple – Efficiently manages data and storage resources according to customer-defined rules, while streamlining overall tape operations Flexible – Engineered with flexibility in mind, can be deployed to meet each enterprise’s unique business requirements  Reliable – Reduces a customer’s exposure by providing superior data protection, end-to-end high availability architecture and closed loop data integrity checking Low Total Cost of Ownership and Investment Protection – Low asset acquisition cost, high-density data center footprint and physical tape energy efficiency keeps customers storage spending within budget For More Information Go To: Oracle.com Tape PageOracle Technology Network Tape Page

    Read the article

  • How do I calculate the amount of tuning needed for my server ?

    - by Low Kian Seong
    I have a server which is running a few discrete Python, Java application which most of the time imports data into a PostGreSQL database. I would like to know from people out there who have experience tuning enterprise grade servers how do i go about calculating in a holistic way the amount of tuning needed for my server for example vm.swappiness, vm.overcommit_ratio and other numerical tunings needed for my server. I tried to enable sar on my server to capture daily numbers but these are more along the lines of total numbers and I can't figure out how to allocate memory for my applications. Help would be appreciated. Thanks.

    Read the article

  • How can I see logs in a server after a kernel panic hang ?

    - by Low Kian Seong
    I am running a production gentoo Linux machine, and recently there was a situation where the server hung in my co-located premises and when I got there I noticed that the server was hung on what appeared to be a kernel panic hang. I rebooted the machine with a hard reboot and was disappointed to find out that I could not find a shred of evidence anywhere on why the machine hung. Is it true that when I do a hard reboot the messages itself will get lost or is there a setting I can do somewhere say in syslog-ng or maybe in sysctl to at least preserve the error log so that I can prevent such mishaps from happening in the future ? I am running a 2.6.x kernel by the way. Thanks in advance.

    Read the article

  • How can I see logs in a server after a kernel panic hang?

    - by Low Kian Seong
    I am running a production gentoo Linux machine, and recently there was a situation where the server hung in my co-located premises and when I got there I noticed that the server was hung on what appeared to be a kernel panic hang. I rebooted the machine with a hard reboot and was disappointed to find out that I could not find a shred of evidence anywhere on why the machine hung. Is it true that when I do a hard reboot the messages itself will get lost or is there a setting I can do somewhere say in syslog-ng or maybe in sysctl to at least preserve the error log so that I can prevent such mishaps from happening in the future ? I am running a 2.6.x kernel by the way. Thanks in advance.

    Read the article

  • no A record show in the answer section in dig results

    - by eric low
    To check the record for the domain, run dig with domain name as the parameter. dig example.com any I get the below result. Why there is no A record show in the result. What did i do wrong during the setup. Please advice what suppose to look into it. Hope everyone can help me to resolve the case asap. ; <<>> DiG 9.9.3-P2 <<>> example.com any ;; global options: +cmd ;; Got answer: ;; ->>HEADER<<- opcode: QUERY, status: NOERROR, id: 44674 ;; flags: qr rd ra; QUERY: 1, ANSWER: 8, AUTHORITY: 4, ADDITIONAL: 1 ;; OPT PSEUDOSECTION: ; EDNS: version: 0, flags:; udp: 4096 ;; QUESTION SECTION: ;example.com. IN ANY ;; ANSWER SECTION: example.com. 3489 IN MX 100 biz.mail.com. example.com. 3482 IN NS ns1.domain.com. example.com. 3482 IN NS ns2.domain.com. ;; AUTHORITY SECTION: example.com. 3482 IN NS ns2.domain.com. example.com. 3482 IN NS ns1.domain.com. ;; Query time: 0 msec ;; SERVER: xxx.252.xxx.xxx#53(xxx.252.xxx.xxx) ;; WHEN: Wed Oct 30 04:48:34 CDT 2013 ;; MSG SIZE rcvd: 349

    Read the article

  • What is the best log rotator for Python wsgi applications ?

    - by Low Kian Seong
    I am running a wsgi based application that has concurrent users accessing it. For my logs needs I tried logrotate but found that logrotate is not too friendly to Python applications, so I tried using RotatingFileHandler and even worse found my logs all chopped up and part of it went missing! I am considering ConcurrentRotatingFileHandler, my question is, has anyone out there experienced the same thing and better yet do you have any battle tested solution for Python wsgi, concurrently accessed applications?

    Read the article

  • What is the best way to handle the multitude of different logs created all around the place?

    - by Low Kian Seong
    I run a few applications which creates their own logs. Then I run cron scripts on the same server to do importing of data for my app. When these cron errors out, the default is it sends emails to the user that runs the cron job. There are just too many places that I need to check the logs and mails for stuff that might have potentially went wrong. My question is, what is the best way to do this or even better is like a log parser application which will go through all the system logs when something really goes wrong instead of me having to go through it daily?

    Read the article

  • What is the best free or low-cost Java reporting library (e.g. BIRT, JasperReports, etc.) for making

    - by Max3000
    I want to print, email and write to PDF very simple reports. The reports are basically a list of items, divided in various sections/columns. The sections are not necessarily identical. Think newspaper. I just wasted a solid 2 days of work trying to make this kind of reports using JasperReports. I find that Jasper is great for outputing "normalized" data. The kind that would come out of a database for instance, each row neatly describing an item and each item printed on a line. I'm simplifying a bit but that's the idea. However, given what I want to do I always ended up completely lost. Data not being displayed for no apparent reason, columns of texts never the correct size, column positioning always ending up incorrect, pagination not sanely possible (I was never able to figure it out; the FAQ gives an obscure workaround), etc. I came to the conclusion that Jasper is really not built to make the kind of reports I want. Am I missing something? I'm ready to pay for a tool, as long as the price is reasonable. By reasonable I mean a few $100s. Thanks. EDIT: To answer cetus, here is more information about the report I made in Jasper. What I want is something like this: text text text text ------------------- text | text text |---------- text | text text | text --------| text text |---------- text | text What I made in jasper is this: (detail band) subreport | subreport ------------------------------------ subreport | subreport ------------------------------------ subreport | subreport The subreports are all the same actual report. This report has one field (called "field") and basically just prints this field in a detail band. Hence, running a single subreport simply lists all items from the datasource. The datasource itself is a simple custom JRDatasource containing a collection of strings in the field "field". The datasource iterates over the collection until there are no more strings. Each subreport has its own datasource. I tried many different variations of the above, with all sorts of different properties for the report, subreports, etc. IMO, this is fairly simple stuff. However, the problems I encounter are as follows: Subreports starting from the 3rd don't show up when their position type is 'float'. They do show up when they have 'fix relative to top'. However, I don't want to do this because the first two subreports can be of any length. I can't make each subreport to stretch according to its own length. Instead, they either don't stretch at all (which is not desirable because they have different lenghts) or they stretch according to the longest subreport. This makes a weird layout for sure. Pagination doesn't happen. If some subreports fall outside the page, they simple don't show. One alternative is to increase the 'page height' considerably and the 'detail band height' accordingly. However, in this case it is not really possibly to know the total height in advance. So I'm stuck with calculating/guessing it myself, before the report is even generated. More importantly, long reports end up on one page and this is not acceptable (the printout text is too small, it's ugly/non-professional to have different reports with different PDF page lengths, etc.). BTW, I used iReport so it's possibly limitations of iReport I'm listing here and not of Jasper itself. That's one of the things I'm trying to find out asking this question here. One alternative would be to generate the jrxml myself with just static text but I'm afraid I'll encounter the very same limitations. Anyway, I just generally wasted so much time getting anything done with Jasper that I can't help thinking its not the right tool for the job. (Not to say that Jasper doesn't excel in what it's good at).

    Read the article

  • Understanding the value of Customer Experience & Loyalty for the Telecommunications Industry

    - by raul.goycoolea
    Worried by economic woes and market forces, especially in mature markets, communications service providers (CSPs) increasingly focus on improving customer experience. In fact, it seems difficult to find a major message by a C-level executive in the developed world that does not include something on "meeting and exceeding customers' needs". Frequently in customer satisfaction studies by prominent firms, CSPs fall short of the leadership demonstrated by other industries that take customer-centric approaches to their bottom-line strategies. Consider the following:Despite the continued impact of global economic crisis, in July 2010, Apple Computer posted record revenue and net quarterly profit. Those who attribute the results primarily to the iPhone 4 launch should note that Apple also shipped around 30% more Macintosh computers than the same period the previous year. Even sales of the iPod line increased by 8% in a highly commoditized, shrinking media player market. Finally, Apple began selling iPads during the quarter, with total sales of more than 3 million units. What does Apple have that the others lack? Well, some great products (and services) to be sure, but it also excels at customer service and support, marketing, and distribution, and has one of the strongest brands globally. Its products are useful, simple to use, easy to acquire and augment, high quality, and considered very cool. They also evoke such an emotional response from many of Apple's customers, which they turn up their noses at competitive products.In other words, Apple appears to have mastered virtually every aspect of customer experience and the resultant loyalty of its customer base - even in difficult financial times. Through that unwavering customer focus, Apple continues to drive its revenues and profits to new heights. Other customer loyalty leaders like Wal-Mart, Google, Toyota and Honda are also doing well by focusing on customer experience as an essential driver of profitability. Service providers should note this performance and ask themselves how they might leverage the same principles to increase their own profitability. After all, that is what customer experience and loyalty are all about: profitability.To successfully manage all the critical touch points of customer experience, CSPs must shun the one-size-fits-all approach. They can no longer afford to view customer service fundamentally as an act of altruism - which mentality dates back to the industry's civil service days, when CSPs were typically government organizations that were critical to economic development and public safety.As regulators and public officials have pushed, and continue to push, service providers to new heights of reliability - using incentives and punishments - most CSPs already have some of the fundamental building blocks of customer service in place. Yet despite that history and experience, service providers still lag other industries in providing what is seen as good customer service.As we observed in the TMF's 2009 Insights Research report, Customer Experience Management: Driving Loyalty & Profitability there has been resurgence in interest by CSPs. More and more of them have stated ambitions to catch up other industries, and they are realizing that good customer service is a powerful strategy for increasing business performance and profitability, not an act of good will.CSPs are recognizing the connection between customer experience and profitability, as demonstrated in many studies. For example, according to research by Bain & Company, a 5 percent improvement in customer retention rates can yield as much as a 75 percent increase in profits for companies across a range of industries.After decades of customer experience strategy formulation, Bain partner and business author, Frederick Reichheld, considers "would you recommend us to a friend?" as the ultimate question for a customer. How many times have you or your friends recommended an iPod, iPhone or a Mac? What do your children recommend to their peers? Their peers to them?There are certain steps service providers have to take to create more personalized relationships with their customers, as well as reduce churn and increase profitability, all while becoming leaner and more agile. First, they have to define customer experience, we define it as the result of the sum of observations, perceptions, thoughts and feelings arising from interactions and relationships between customers and their service provider(s). Virtually every customer touch point - whether directly or indirectly linked to service providers and their partners - contributes to customer perception, satisfaction, loyalty, and ultimately profitability. Gaining leadership in customer experience and satisfaction will not be a simple task, as it is affected by virtually every customer-facing aspect of the service provider, and in turn impacts the service provider deeply - especially on the all-important bottom line. The scope of issues affecting customer experience is complex and dynamic.With new services, devices and applications extending the basis of customer experience to domains beyond the direct control of the service provider, it is likely to increase in complexity and dynamism.Customer loyalty = increased profitsAs stated earlier, customer experience programs are not fundamentally altruistic exercises, but a strategic means of improving competitiveness and profitability in the short and long term. Loyalty is essential to deriving long term profits from customers.Some of the earliest loyalty programs date back to the 1930s, when packaged goods companies offered embedded coupons for rewards to buyers, and eventually retail chains began offering reward programs to frequent shoppers. These programs continued for decades but were leapfrogged in the 1980s by more aggressive programs from the airlines.This movement was led by American Airlines, which launched the first full-scale loyalty marketing program of the modern era with the AAdvantage frequent flyer scheme. It was the first to reward frequent fliers with notional air miles that could be accumulated and later redeemed for free travel. Figure 1: Opportunities example of Customer loyalty driven profitOther airlines and travel providers were quick to grasp the incredible value of providing customers with an incentive to use their company exclusively. Within a few years, dozens of travel industry companies launched similar initiatives and now loyalty programs are achieving near-ubiquity in many service industries, especially those in which it is difficult to differentiate offerings by product attributes.The belief is that increased profitability will result from customer retention efforts because:•    The cost of acquisition occurs only at the beginning of a relationship: the longer the relationship, the lower the amortized cost;•    Account maintenance costs decline as a percentage of total costs, or as a percentage of revenue, over the lifetime of the relationship;•    Long term customers tend to be less inclined to switch and less price sensitive which can result in stable unit sales volume and increases in dollar-sales volume;•    Long term customers may initiate word-of-mouth promotions and referrals, which cost the company nothing and arguably are the most effective form of advertising;•    Long-term customers are more likely to buy ancillary products and higher margin supplemental products;•    Long term customers tend to be satisfied with their relationship with the company and are less likely to switch to competitors, making market entry or competitors gaining market share difficult;•    Regular customers tend to be less expensive to service, as they are familiar with the processes involved, require less 'education', and are consistent in their order placement;•    Increased customer retention and loyalty makes the employees' jobs easier and more satisfying. In turn, happy employees feed back into higher customer satisfaction in a virtuous circle. Figure 2: The virtuous circle of customer loyaltyFigure 2 represents a high-level example of a virtuous cycle driven by customer satisfaction and loyalty, depicting how superiority in product and service offerings, as well as strong customer support by competent employees, lead to higher sales and ultimately profitability. As stated above, this is not a new concept, but succeeding with it is difficult. It has eluded many a company driven to achieve profitability goals. Of course, for this circle to be virtuous, the customer relationship(s) must be profitable.Trying to maintain the loyalty of unprofitable customers is not a viable business strategy. It is, therefore, important that marketers can assess the profitability of each customer (or customer segment), and either improve or terminate relationships that are not profitable. This means each customer's 'relationship costs' must be understood and compared to their 'relationship revenue'. Customer lifetime value (CLV) is the most commonly used metric here, as it is generally accepted as a representation of exactly how much each customer is worth in monetary terms, and therefore a determinant of exactly how much a service provider should be willing to spend to acquire or retain that customer.CLV models make several simplifying assumptions and often involve the following inputs:•    Churn rate represents the percentage of customers who end their relationship with a company in a given period;•    Retention rate is calculated by subtracting the churn rate percentage from 100;•    Period/horizon equates to the units of time into which a customer relationship can be divided for analysis. A year is the most commonly used period for this purpose. Customer lifetime value is a multi-period calculation, often projecting three to seven years into the future. In practice, analysis beyond this point is viewed as too speculative to be reliable. The model horizon is the number of periods used in the calculation;•    Periodic revenue is the amount of revenue collected from a customer in a given period (though this is often extended across multiple periods into the future to understand lifetime value), such as usage revenue, revenues anticipated from cross and upselling, and often some weighting for referrals by a loyal customer to others; •    Retention cost describes the amount of money the service provider must spend, in a given period, to retain an existing customer. Again, this is often forecast across multiple periods. Retention costs include customer support, billing, promotional incentives and so on;•    Discount rate means the cost of capital used to discount future revenue from a customer. Discounting is an advanced method used in more sophisticated CLV calculations;•    Profit margin is the projected profit as a percentage of revenue for the period. This may be reflected as a percentage of gross or net profit. Again, this is generally projected across the model horizon to understand lifetime value.A strong focus on managing these inputs can help service providers realize stronger customer relationships and profits, but there are some obstacles to overcome in achieving accurate calculations of CLV, such as the complexity of allocating costs across the customer base. There are many costs that serve all customers which must be properly allocated across the base, and often a simple proportional allocation across the whole base or a segment may not accurately reflect the true cost of serving that customer;  This is made worse by the fragmentation of customer information, which is likely to be across a variety of product or operations groups, and may be difficult to aggregate due to different representations.In addition, there is the complexity of account relationships and structures to take into consideration. Complex account structures may not be understood or properly represented. For example, a profitable customer may have a separate account for a second home or another family member, which may appear to be unprofitable. If the service provider cannot relate the two accounts, CLV is not properly represented and any resultant cancellation of the apparently unprofitable account may result in the customer churning from the profitable one.In summary, if service providers are to realize strong customer relationships and their attendant profits, there must be a very strong focus on data management. This needs to be coupled with analytics that help business managers and those who work in customer-facing functions offer highly personalized solutions to customers, while maintaining profitability for the service provider. It's clear that acquiring new customers is expensive. Advertising costs, campaign management expenses, promotional service pricing and discounting, and equipment subsidies make a serious dent in a new customer's profitability. That is especially true given the rising subsidies for Smartphone users, which service providers hope will result in greater profits from profits from data services profitability in future.  The situation is made worse by falling prices and greater competition in mature markets.Customer acquisition through industry consolidation isn't cheap either. A North American service provider spent about $2,000 per subscriber in its acquisition of a smaller company earlier this year. While this has allowed it to leapfrog to become the largest mobile service provider in the country, it required a total investment of more than $28 billion (including assumption of the acquiree's debt).While many operating cost synergies clearly made this deal more attractive to the acquiring company, this is certainly an expensive way to acquire customers: the cost per subscriber in this case is not out of line with the prices others have paid for acquisitions.While growth by acquisition certainly increases overall revenues, it often creates tremendous challenges for profitability. Organic growth through increased customer loyalty and retention is a more effective driver of profit, as well as a stronger predictor of future profitability. Service providers, especially those in mature markets, are increasingly recognizing this and taking steps toward a creating a more personalized, flexible and satisfying experience for their customers.In summary, the clearest path to profitability for companies in virtually all industries is through customer retention and maximization of lifetime value. Service providers would do well to recognize this and focus attention on profitable customer relationships.

    Read the article

  • CBO????????

    - by Liu Maclean(???)
    ???Itpub????????CBO??????????, ????????: SQL> create table maclean1 as select * from dba_objects; Table created. SQL> update maclean1 set status='INVALID' where owner='MACLEAN'; 2 rows updated. SQL> commit; Commit complete. SQL> create index ind_maclean1 on maclean1(status); Index created. SQL> exec dbms_stats.gather_table_stats('SYS','MACLEAN1',cascade=>true); PL/SQL procedure successfully completed. SQL> explain plan for select * from maclean1 where status='INVALID'; Explained. SQL> set linesize 140 pagesize 1400 SQL> select * from table(dbms_xplan.display()); PLAN_TABLE_OUTPUT --------------------------------------------------------------------------- Plan hash value: 987568083 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 11320 | 1028K| 85 (0)| 00:00:02 | |* 1 | TABLE ACCESS FULL| MACLEAN1 | 11320 | 1028K| 85 (0)| 00:00:02 | ------------------------------------------------------------------------------ Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter("STATUS"='INVALID') 13 rows selected. 10053 trace Access path analysis for MACLEAN1 *************************************** SINGLE TABLE ACCESS PATH   Single Table Cardinality Estimation for MACLEAN1[MACLEAN1]   Column (#10): STATUS(     AvgLen: 7 NDV: 2 Nulls: 0 Density: 0.500000   Table: MACLEAN1  Alias: MACLEAN1     Card: Original: 22639.000000  Rounded: 11320  Computed: 11319.50  Non Adjusted: 11319.50   Access Path: TableScan     Cost:  85.33  Resp: 85.33  Degree: 0       Cost_io: 85.00  Cost_cpu: 11935345       Resp_io: 85.00  Resp_cpu: 11935345   Access Path: index (AllEqRange)     Index: IND_MACLEAN1     resc_io: 185.00  resc_cpu: 8449916     ix_sel: 0.500000  ix_sel_with_filters: 0.500000     Cost: 185.24  Resp: 185.24  Degree: 1   Best:: AccessPath: TableScan          Cost: 85.33  Degree: 1  Resp: 85.33  Card: 11319.50  Bytes: 0 ?????10053????????????,?????Density = 0.5 ?? 1/ NDV ??? ??????????????STATUS='INVALID"???????????, ????????????????? ????”STATUS”=’INVALID’ condition???2?,?status??????,??????dbms_stats?????????????,???CBO????INDEX Range ind_maclean1,???????,??????opitimizer?????? ?????????????????????????,????????,??????????status=’INVALID’???????card??,????????: [oracle@vrh4 ~]$ sqlplus / as sysdba SQL*Plus: Release 11.2.0.2.0 Production on Mon Oct 17 19:15:45 2011 Copyright (c) 1982, 2010, Oracle. All rights reserved. Connected to: Oracle Database 11g Enterprise Edition Release 11.2.0.2.0 - 64bit Production With the Partitioning, OLAP, Data Mining and Real Application Testing options SQL> select * from v$version; BANNER -------------------------------------------------------------------------------- Oracle Database 11g Enterprise Edition Release 11.2.0.2.0 - 64bit Production PL/SQL Release 11.2.0.2.0 - Production CORE 11.2.0.2.0 Production TNS for Linux: Version 11.2.0.2.0 - Production NLSRTL Version 11.2.0.2.0 - Production SQL> show parameter optimizer_fea NAME TYPE VALUE ------------------------------------ ----------- ------------------------------ optimizer_features_enable string 11.2.0.2 SQL> select * from global_name; GLOBAL_NAME -------------------------------------------------------------------------------- www.oracledatabase12g.com & www.askmaclean.com SQL> drop table maclean; Table dropped. SQL> create table maclean as select * from dba_objects; Table created. SQL> update maclean set status='INVALID' where owner='MACLEAN'; 2 rows updated. SQL> commit; Commit complete. SQL> create index ind_maclean on maclean(status); Index created. SQL> exec dbms_stats.gather_table_stats('SYS','MACLEAN',cascade=>true, method_opt=>'FOR ALL COLUMNS SIZE 2'); PL/SQL procedure successfully completed. ???????2?bucket????, ??????????????? ???Quest???Guy Harrison???????FREQUENCY????????,??????: rem rem Generate a histogram of data distribution in a column as recorded rem in dba_tab_histograms rem rem Guy Harrison Jan 2010 : www.guyharrison.net rem rem hexstr function is from From http://asktom.oracle.com/pls/asktom/f?p=100:11:0::::P11_QUESTION_ID:707586567563 set pagesize 10000 set lines 120 set verify off col char_value format a10 heading "Endpoint|value" col bucket_count format 99,999,999 heading "bucket|count" col pct format 999.99 heading "Pct" col pct_of_max format a62 heading "Pct of|Max value" rem col endpoint_value format 9999999999999 heading "endpoint|value" CREATE OR REPLACE FUNCTION hexstr (p_number IN NUMBER) RETURN VARCHAR2 AS l_str LONG := TO_CHAR (p_number, 'fm' || RPAD ('x', 50, 'x')); l_return VARCHAR2 (4000); BEGIN WHILE (l_str IS NOT NULL) LOOP l_return := l_return || CHR (TO_NUMBER (SUBSTR (l_str, 1, 2), 'xx')); l_str := SUBSTR (l_str, 3); END LOOP; RETURN (SUBSTR (l_return, 1, 6)); END; / WITH hist_data AS ( SELECT endpoint_value,endpoint_actual_value, NVL(LAG (endpoint_value) OVER (ORDER BY endpoint_value),' ') prev_value, endpoint_number, endpoint_number, endpoint_number - NVL (LAG (endpoint_number) OVER (ORDER BY endpoint_value), 0) bucket_count FROM dba_tab_histograms JOIN dba_tab_col_statistics USING (owner, table_name,column_name) WHERE owner = '&owner' AND table_name = '&table' AND column_name = '&column' AND histogram='FREQUENCY') SELECT nvl(endpoint_actual_value,endpoint_value) endpoint_value , bucket_count, ROUND(bucket_count*100/SUM(bucket_count) OVER(),2) PCT, RPAD(' ',ROUND(bucket_count*50/MAX(bucket_count) OVER()),'*') pct_of_max FROM hist_data; WITH hist_data AS ( SELECT endpoint_value,endpoint_actual_value, NVL(LAG (endpoint_value) OVER (ORDER BY endpoint_value),' ') prev_value, endpoint_number, endpoint_number, endpoint_number - NVL (LAG (endpoint_number) OVER (ORDER BY endpoint_value), 0) bucket_count FROM dba_tab_histograms JOIN dba_tab_col_statistics USING (owner, table_name,column_name) WHERE owner = '&owner' AND table_name = '&table' AND column_name = '&column' AND histogram='FREQUENCY') SELECT hexstr(endpoint_value) char_value, bucket_count, ROUND(bucket_count*100/SUM(bucket_count) OVER(),2) PCT, RPAD(' ',ROUND(bucket_count*50/MAX(bucket_count) OVER()),'*') pct_of_max FROM hist_data ORDER BY endpoint_value; ?????,??????????FREQUENCY?????: ??dbms_stats ?????STATUS=’INVALID’ bucket count=9 percent = 0.04 ,??????10053 trace????????: SQL> explain plan for select * from maclean where status='INVALID'; Explained. SQL>  select * from table(dbms_xplan.display()); PLAN_TABLE_OUTPUT ------------------------------------- Plan hash value: 3087014066 ------------------------------------------------------------------------------------------- | Id  | Operation                   | Name        | Rows  | Bytes | Cost (%CPU)| Time     | ------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT            |             |     9 |   837 |     2   (0)| 00:00:01 | |   1 |  TABLE ACCESS BY INDEX ROWID| MACLEAN     |     9 |   837 |     2   (0)| 00:00:01 | |*  2 |   INDEX RANGE SCAN          | IND_MACLEAN |     9 |       |     1   (0)| 00:00:01 | ------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    2 - access("STATUS"='INVALID') ??????????????CBO???????STATUS=’INVALID’?cardnality?? , ??????????? ,??index range scan??Full table scan? ????????????????10053 trace: SQL> alter system flush shared_pool; System altered. SQL> oradebug setmypid; Statement processed. SQL> oradebug event 10053 trace name context forever ,level 1; Statement processed. SQL> explain plan for select * from maclean where status='INVALID'; Explained. SINGLE TABLE ACCESS PATH Single Table Cardinality Estimation for MACLEAN[MACLEAN] Column (#10): NewDensity:0.000199, OldDensity:0.000022 BktCnt:22640, PopBktCnt:22640, PopValCnt:2, NDV:2 ???NewDensity= bucket_count / SUM(bucket_count) /2 Column (#10): STATUS( AvgLen: 7 NDV: 2 Nulls: 0 Density: 0.000199 Histogram: Freq #Bkts: 2 UncompBkts: 22640 EndPtVals: 2 Table: MACLEAN Alias: MACLEAN Card: Original: 22640.000000 Rounded: 9 Computed: 9.00 Non Adjusted: 9.00 Access Path: TableScan Cost: 85.30 Resp: 85.30 Degree: 0 Cost_io: 85.00 Cost_cpu: 10804625 Resp_io: 85.00 Resp_cpu: 10804625 Access Path: index (AllEqRange) Index: IND_MACLEAN resc_io: 2.00 resc_cpu: 20763 ix_sel: 0.000398 ix_sel_with_filters: 0.000398 Cost: 2.00 Resp: 2.00 Degree: 1 Best:: AccessPath: IndexRange Index: IND_MACLEAN Cost: 2.00 Degree: 1 Resp: 2.00 Card: 9.00 Bytes: 0 ???????????2 bucket?????CBO????????????,???????????????????,???dbms_stats.DEFAULT_METHOD_OPT????????????????????? ???dbms_stats?????????????????????col_usage$??????predicate???????,??col_usage$??<????????SMON??(?):??col_usage$????>? ??????????dbms_stats????????,col_usage$????????????predicate???,??dbms_stats??????????????????, ?: SQL> drop table maclean; Table dropped. SQL> create table maclean as select * from dba_objects; Table created. SQL> update maclean set status='INVALID' where owner='MACLEAN'; 2 rows updated. SQL> commit; Commit complete. SQL> create index ind_maclean on maclean(status); Index created. ??dbms_stats??method_opt??maclean? SQL> exec dbms_stats.gather_table_stats('SYS','MACLEAN'); PL/SQL procedure successfully completed. @histogram.sql Enter value for owner: SYS old  12:    WHERE owner = '&owner' new  12:    WHERE owner = 'SYS' Enter value for table: MACLEAN old  13:      AND table_name = '&table' new  13:      AND table_name = 'MACLEAN' Enter value for column: STATUS old  14:      AND column_name = '&column' new  14:      AND column_name = 'STATUS' no rows selected ????col_usage$?????,????????status????? declare begin for i in 1..500 loop execute immediate ' alter system flush shared_pool'; DBMS_STATS.FLUSH_DATABASE_MONITORING_INFO; execute immediate 'select count(*) from maclean where status=''INVALID'' ' ; end loop; end; / PL/SQL procedure successfully completed. SQL> select obj# from obj$ where name='MACLEAN';       OBJ# ----------      97215 SQL> select * from  col_usage$ where  OBJ#=97215;       OBJ#    INTCOL# EQUALITY_PREDS EQUIJOIN_PREDS NONEQUIJOIN_PREDS RANGE_PREDS LIKE_PREDS NULL_PREDS TIMESTAMP ---------- ---------- -------------- -------------- ----------------- ----------- ---------- ---------- ---------      97215          1              1              0                 0           0          0          0 17-OCT-11      97215         10            499              0                 0           0          0          0 17-OCT-11 SQL> exec dbms_stats.gather_table_stats('SYS','MACLEAN'); PL/SQL procedure successfully completed. @histogram.sql Enter value for owner: SYS Enter value for table: MACLEAN Enter value for column: STATUS Endpoint        bucket         Pct of value            count     Pct Max value ---------- ----------- ------- -------------------------------------------------------------- INVALI               2     .04 VALIC3           5,453   99.96  *************************************************

    Read the article

  • What Color is your Jetpack ?

    - by JoshReuben
    I’m a programmer, Im approaching 40, and I’m fairly decent at my job – I’ll keep doing what I’m doing for as long as they let me!   So what are your career options if you know how to code? A Programmer could be ..   An Algorithm developer Pros Interesting High barriers of entry, potential for startup competitive factor Cons Do you have the skill, qualifications? What are working conditions n this mystery niche ? micro-focus An Academic Pros Low pressure Job security – or is this an illusion ? Cons Low Pay Need a PhD A Software Architect Pros: strategic, rather than tactical Setting technology platform and high level vision You say how it should work, others have to figure out why its not working the way its supposed to ! broad view – you are paid to learn (how do you con people into paying for you to learn ??) Cons: Glorified developer – more often than not! competitive – everyone wants to do it ! loose touch with underlying tech in tough times, first guy to get the axe ! A Software Engineer Pros: interesting, always more to learn fun I can do it Fallback Cons: Nothing new under the sun – been there, done that Dealing with poor requirements, deadlines, other peoples code, overtime C#, XAML, Web - Low barriers of entry –> à race to the bottom A Team leader Pros: Setting code standards and proposing technology choices Cons: Glorified developer – more often than not! Inspecting other peoples code and debugging the problems they cannot fix Dealing with mugbies and prima donas Responsible for QA of others A Project Manager Pros No need for debugging other peoples code Cons Low barrier of entry High pressure Responsible for QA of others Loosing touch with technology A lot of bullshit meetings Have to be an asshole A Product Manager Pros No need for debugging other peoples code Learning new skillset of sales and marketing Cons Travel (I'm a family man) May need to know the bs details of an uninteresting product things I want to work with: AI, algorithms, Numerical Computing, Mathematica, C++ AMP – unfortunately, the work here is few & far between. VS & TFS Extensibility, DSLs (Workflow , Lightswitch), Code Generation – one day, code will write code ! Unity3D, WebGL – fun, fun, fun ! Modern Web – Knockout, SignalR, MVC, Node.Js ??? (tentative – I'll wait until things stabilize as this area is undergoing a pre-Cambrian explosion) Things I don’t want to work with: (but will if I'm asked to !) C# – same old, same old – not learning anything new here Old code – blech ! Environment with code & fix mentality , ad hoc requirements, excessive overtime Pc support, System administration – even after 20 years, people still ask you to do this sometimes ! debugging – my skills are just not there yet Oracle Old tech: VB 6, XSLT, WinForms, Net 3.51 or less Old style Web dev Information Systems: ASP.NET webforms, Reporting services / crystal reports, SQL Server CRUD with manual data layer, XAML MVVM – variations of the same concept, ad nauseaum. Low barriers of entry –> race to the bottom.  Metro – an elegant API coupled to a horrendous UX – I'll wait for market penetration viability before investing further in this.   Conclusion So if you are in a slump, take heart: Programming is a great career choice compared to every other job !

    Read the article

  • Fast Data - Big Data's achilles heel

    - by thegreeneman
    At OOW 2013 in Mark Hurd and Thomas Kurian's keynote, they discussed Oracle's Fast Data software solution stack and discussed a number of customers deploying Oracle's Big Data / Fast Data solutions and in particular Oracle's NoSQL Database.  Since that time, there have been a large number of request seeking clarification on how the Fast Data software stack works together to deliver on the promise of real-time Big Data solutions.   Fast Data is a software solution stack that deals with one aspect of Big Data, high velocity.   The software in the Fast Data solution stack involves 3 key pieces and their integration:  Oracle Event Processing, Oracle Coherence, Oracle NoSQL Database.   All three of these technologies address a high throughput, low latency data management requirement.   Oracle Event Processing enables continuous query to filter the Big Data fire hose, enable intelligent chained events to real-time service invocation and augments the data stream to provide Big Data enrichment. Extended SQL syntax allows the definition of sliding windows of time to allow SQL statements to look for triggers on events like breach of weighted moving average on a real-time data stream.    Oracle Coherence is a distributed, grid caching solution which is used to provide very low latency access to cached data when the data is too big to fit into a single process, so it is spread around in a grid architecture to provide memory latency speed access.  It also has some special capabilities to deploy remote behavioral execution for "near data" processing.   The Oracle NoSQL Database is designed to ingest simple key-value data at a controlled throughput rate while providing data redundancy in a cluster to facilitate highly concurrent low latency reads.  For example, when large sensor networks are generating data that need to be captured while analysts are simultaneously extracting the data using range based queries for upstream analytics.  Another example might be storing cookies from user web sessions for ultra low latency user profile management, also leveraging that data using holistic MapReduce operations with your Hadoop cluster to do segmented site analysis.  Understand how NoSQL plays a critical role in Big Data capture and enrichment while simultaneously providing a low latency and scalable data management infrastructure thru clustered, always on, parallel processing in a shared nothing architecture. Learn how easily a NoSQL cluster can be deployed to provide essential services in industry specific Fast Data solutions. See these technologies work together in a demonstration highlighting the salient features of these Fast Data enabling technologies in a location based personalization service. The question then becomes how do these things work together to deliver an end to end Fast Data solution.  The answer is that while different applications will exhibit unique requirements that may drive the need for one or the other of these technologies, often when it comes to Big Data you may need to use them together.   You may have the need for the memory latencies of the Coherence cache, but just have too much data to cache, so you use a combination of Coherence and Oracle NoSQL to handle extreme speed cache overflow and retrieval.   Here is a great reference to how these two technologies are integrated and work together.  Coherence & Oracle NoSQL Database.   On the stream processing side, it is similar as with the Coherence case.  As your sliding windows get larger, holding all the data in the stream can become difficult and out of band data may need to be offloaded into persistent storage.  OEP needs an extreme speed database like Oracle NoSQL Database to help it continue to perform for the real time loop while dealing with persistent spill in the data stream.  Here is a great resource to learn more about how OEP and Oracle NoSQL Database are integrated and work together.  OEP & Oracle NoSQL Database.

    Read the article

  • Proving What You are Worth

    - by Ted Henson
    Here is a challenge for everyone. Just about everyone has been asked to provide or calculate the Return on Investment (ROI), so I will assume everyone has a method they use. The problem with stopping once you have an ROI is that those in the C-Suite probably do not care about the ROI as much as Return on Equity (ROE). Shareholders are mostly concerned with their return on the money the invested. Warren Buffett looks at ROE when deciding whether to make a deal or not. This article will outline how you can add more meaning to your ROI and show how you can potentially enhance the ROE of the company.   First I want to start with a base definition I am using for ROI and ROE. Return on investment (ROI) and return on equity (ROE) are ways to measure management effectiveness, parts of a system of measures that also includes profit margins for profitability, price-to-earnings ratio for valuation, and various debt-to-equity ratios for financial strength. Without a set of evaluation metrics, a company's financial performance cannot be fully examined by investors. ROI and ROE calculate the rate of return on a specific investment and the equity capital respectively, assessing how efficient financial resources have been used. Typically, the best way to improve financial efficiency is to reduce production cost, so that will be the focus. Now that the challenge has been made and items have been defined, let’s go deeper. Most research about implementation stops short at system start-up and seldom addresses post-implementation issues. However, we know implementation is a continuous improvement effort, and continued efforts after system start-up will influence the ultimate success of a system.   Most UPK ROI’s I have seen only include the cost savings in developing the training material. Some will also include savings based on reduced Help Desk calls. Using just those values you get a good ROI. To get an ROE you need to go a little deeper. Typically, the best way to improve financial efficiency is to reduce production cost, which is the purpose of implementing/upgrading an enterprise application. Let’s assume the new system is up and running and all users have been properly trained and are comfortable using the system. You provide senior management with your ROI that justifies the original cost. What you want to do now is develop a good base value to a measure the current efficiency. Using usage tracking you can look for various patterns. For example, you may find that users that are accessing UPK assistance are processing a procedure, such as entering an order, 5 minutes faster than those that don’t.  You do some research and discover each minute saved in processing a claim saves the company one dollar. That translates to the company saving five dollars on every transaction. Assuming 100,000 transactions are performed a year, and all users improve their performance, the company will be saving $500,000 a year. That $500,000 can be re-invested, used to reduce debt or paid to the shareholders.   With continued refinement during the life cycle, you should be able to find ways to reduce cost. These are the type of numbers and productivity gains that senior management and shareholders want to see. Being able to quantify savings and increase productivity may also help when seeking a raise or promotion.

    Read the article

  • Alternative to Amazon’s S3 service?

    - by Cory
    Just wondering if there is good alternative to Amazon's S3 service? I like S3 but the bandwidth cost is high. I looked at CouldFiles from Rackspace but the cost is even higher. I don't mind prepaying or having monthly payment in order to reduce the bandwidth cost greatly. Thank you for any help

    Read the article

  • R ggplot2: Arrange facet_grid by non-facet column (and labels using non-facet column)

    - by tommy-o-dell
    I have a couple of questions regarding facetting in ggplot2... Let's say I have a query that returns data that looks like this: (note that it's ordered by Rank asc, Alarm asc and two Alarms have a Rank of 3 because their Totals = 1798 for Week 4, and Rank is set according to Total for Week 4) Rank Week Alarm Total 1 1 BELTWEIGHER HIGH HIGH 1000 1 2 BELTWEIGHER HIGH HIGH 1050 1 3 BELTWEIGHER HIGH HIGH 900 1 4 BELTWEIGHER HIGH HIGH 1800 2 1 MICROWAVE LHS 200 2 2 MICROWAVE LHS 1200 2 3 MICROWAVE LHS 400 2 4 MICROWAVE LHS 1799 3 1 HI PRESS FILTER 2 CLOG SW 1250 3 2 HI PRESS FILTER 2 CLOG SW 1640 3 3 HI PRESS FILTER 2 CLOG SW 1000 3 4 HI PRESS FILTER 2 CLOG SW 1798 3 1 LOW PRESS FILTER 2 CLOG SW 800 3 2 LOW PRESS FILTER 2 CLOG SW 1200 3 3 LOW PRESS FILTER 2 CLOG SW 800 3 4 LOW PRESS FILTER 2 CLOG SW 1798 (duplication code below) Rank = c(rep(1,4),rep(2,4),rep(3,8)) Week = c(rep(1:4,4)) Total = c( 1000,1050,900,1800, 200,1200,400,1799, 1250,1640,1000,1798, 800,1200,800,1798) Alarm = c(rep("BELTWEIGHER HIGH HIGH",4), rep("MICROWAVE LHS",4), rep("HI PRESS FILTER 2 CLOG SW",4), rep("LOW PRESS FILTER 2 CLOG SW",4)) spark <- data.frame(Rank, Week, Alarm, Total) Now when I do this... s <- ggplot(spark, aes(Week, Total)) + opts( panel.background = theme_rect(size = 1, colour = "lightgray"), panel.grid.major = theme_blank(), panel.grid.minor = theme_blank(), axis.line = theme_blank(), axis.text.x = theme_blank(), axis.text.y = theme_blank(), axis.title.x = theme_blank(), axis.title.y = theme_blank(), axis.ticks = theme_blank(), strip.background = theme_blank(), strip.text.y = theme_text(size = 7, colour = "red", angle = 0) ) s + facet_grid(Alarm ~ .) + geom_line() I get this.... Notice that it's facetted according to Alarm and that the facets are arranged alphabetically. Two Questions: How can I can I keep it facetted by alarm but displayed in the correct order? (Rank asc, Alarm asc). Also, how can I keep it facetted by alarm but show labels from Rank instead of Alarm? Note that I can't just facet on Rank because ggplot2 would see only 3 facets to plot where there are really 4 different alarms. Thanks kindly for the help! Tommy

    Read the article

< Previous Page | 34 35 36 37 38 39 40 41 42 43 44 45  | Next Page >