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  • Strategy for avoiding duplicate object ids for data shared across devices using iCloud

    - by rmaddy
    I have a data intensive iOS app that is not using CoreData nor does it support iCloud synching (yet). All of my objects are created with unique keys. I use a simple long long initialized with the current time. Then as I need a new key I increment the value by 1. This has all worked well for a few years with the app running isolated on a single device. Now I want to add support for automatic data sync across devices using iCloud. As my app is written, there is the possibility that two objects created on two different devices could end up with the same key. I need to avoid this possibility. I'm looking for ideas for solving this issue. I have a few requirements that the solution must meet: 1) The key needs to remain a single integral data type. Converting all existing keys to a compound key or to a string or other type would affect the entire code base and likely result in more bugs than it's worth. 2) The solution can't depend on an Internet connection. A user must be able to run the app and add data even with no Internet connection. The data should still resolve properly later when the data syncs through iCloud once a connection is available. I'll accept one exception to this rule. If no other option is available, I may be open to requiring an Internet connection the first time the app's data is initialized. One idea I have been toying around with in my head is logically splitting the integer key into two parts. The high 4 or 5 bits could be used as some sort of device id while the rest represents the actual key. The fuzzy part is figuring out how to come up with non-conflicting device ids that fit in a few bits. This should be viable since I don't need to deal will millions of devices. I just need to deal with the few devices that would be shared by a given iCloud account. I'm open to suggestions. Thanks.

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  • JGoodies HashMap

    - by JohnMcClane
    Hi, I'm trying to build a chart program using presentation model. Using JGoodies for data binding was relatively easy for simple types like strings or numbers. But I can't figure out how to use it on a hashmap. I'll try to explain how the chart works and what my problem is: A chart consists of DataSeries, a DataSeries consists of DataPoints. I want to have a data model and to be able to use different views on the same model (e.g. bar chart, pie chart,...). Each of them consists of three classes. For example: DataPointModel: holds the data model (value, label, category) DataPointViewModel: extends JGoodies PresentationModel. wraps around DataPointModel and holds view properties like font and color. DataPoint: abstract class, extends JComponent. Different Views must subclass and implement their own ui. Binding and creating the data model was easy, but i don't know how to bind my data series model. package at.onscreen.chart; import java.beans.PropertyChangeListener; import java.beans.PropertyChangeSupport; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.HashMap; import java.util.Iterator; public class DataSeriesModel { public static String PROPERTY_DATAPOINT = "dataPoint"; public static String PROPERTY_DATAPOINTS = "dataPoints"; public static String PROPERTY_LABEL = "label"; public static String PROPERTY_MAXVALUE = "maxValue"; /** * holds the data points */ private HashMap dataPoints; /** * the label for the data series */ private String label; /** * the maximum data point value */ private Double maxValue; /** * the model supports property change notification */ private PropertyChangeSupport propertyChangeSupport; /** * default constructor */ public DataSeriesModel() { this.maxValue = Double.valueOf(0); this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); } /** * constructor * @param label - the series label */ public DataSeriesModel(String label) { this.dataPoints = new HashMap(); this.maxValue = Double.valueOf(0); this.label = label; this.propertyChangeSupport = new PropertyChangeSupport(this); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeriesModel(String label, DataPoint[] dataPoints) { this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); this.maxValue = Double.valueOf(0); this.label = label; for (int i = 0; i < dataPoints.length; i++) { this.addDataPoint(dataPoints[i]); } } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeriesModel(String label, Collection dataPoints) { this.dataPoints = new HashMap(); this.propertyChangeSupport = new PropertyChangeSupport(this); this.maxValue = Double.valueOf(0); this.label = label; for (Iterator it = dataPoints.iterator(); it.hasNext();) { this.addDataPoint(it.next()); } } /** * adds a new data point to the series. if the series contains a data point with same id, it will be replaced by the new one. * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { String category = dataPoint.getCategory(); DataPoint oldDataPoint = this.getDataPoint(category); this.dataPoints.put(category, dataPoint); this.setMaxValue(Math.max(this.maxValue, dataPoint.getValue())); this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINT, oldDataPoint, dataPoint); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.dataPoints.get(category); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { DataPoint dataPoint = this.getDataPoint(category); this.dataPoints.remove(category); if (dataPoint != null) { if (dataPoint.getValue() == this.getMaxValue()) { Double maxValue = Double.valueOf(0); for (Iterator it = this.iterator(); it.hasNext();) { DataPoint itDataPoint = it.next(); maxValue = Math.max(itDataPoint.getValue(), maxValue); } this.setMaxValue(maxValue); } } this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINT, dataPoint, null); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.setMaxValue(Double.valueOf(0)); this.dataPoints.clear(); this.propertyChangeSupport.firePropertyChange(PROPERTY_DATAPOINTS, this.getDataPoints(), null); } /** * returns the maximum of all data point values * @return the maximum of all data points */ public Double getMaxValue() { return this.maxValue; } /** * sets the max value * @param maxValue - the max value */ protected void setMaxValue(Double maxValue) { Double oldMaxValue = this.getMaxValue(); this.maxValue = maxValue; this.propertyChangeSupport.firePropertyChange(PROPERTY_MAXVALUE, oldMaxValue, maxValue); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.dataPoints.containsKey(category); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.label; } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.dataPoints.values().iterator(); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.dataPoints.values(); } /** * returns the number of data points in the series * @return the number of data points */ public int getSize() { return this.dataPoints.size(); } /** * adds a PropertyChangeListener * @param listener - the listener */ public void addPropertyChangeListener(PropertyChangeListener listener) { this.propertyChangeSupport.addPropertyChangeListener(listener); } /** * removes a PropertyChangeListener * @param listener - the listener */ public void removePropertyChangeListener(PropertyChangeListener listener) { this.propertyChangeSupport.removePropertyChangeListener(listener); } } package at.onscreen.chart; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.Iterator; import com.jgoodies.binding.PresentationModel; public class DataSeriesViewModel extends PresentationModel { /** * default constructor */ public DataSeriesViewModel() { super(new DataSeriesModel()); } /** * constructor * @param label - the series label */ public DataSeriesViewModel(String label) { super(new DataSeriesModel(label)); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeriesViewModel(String label, DataPoint[] dataPoints) { super(new DataSeriesModel(label, dataPoints)); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeriesViewModel(String label, Collection dataPoints) { super(new DataSeriesModel(label, dataPoints)); } /** * full constructor * @param model - the data series model */ public DataSeriesViewModel(DataSeriesModel model) { super(model); } /** * adds a data point to the series * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { this.getBean().addDataPoint(dataPoint); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.getBean().contains(category); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.getBean().getDataPoint(category); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.getBean().getDataPoints(); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.getBean().getLabel(); } /** * sets the max value * @param maxValue - the max value */ public Double getMaxValue() { return this.getBean().getMaxValue(); } /** * returns the number of data points in the series * @return the number of data points */ public int getSize() { return this.getBean().getSize(); } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.getBean().iterator(); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.getBean().removeAll(); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { this.getBean().removeDataPoint(category); } } package at.onscreen.chart; import java.beans.PropertyChangeEvent; import java.beans.PropertyChangeListener; import java.beans.PropertyVetoException; import java.util.Collection; import java.util.Iterator; import javax.swing.JComponent; public abstract class DataSeries extends JComponent implements PropertyChangeListener { /** * the model */ private DataSeriesViewModel model; /** * default constructor */ public DataSeries() { this.model = new DataSeriesViewModel(); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * constructor * @param label - the series label */ public DataSeries(String label) { this.model = new DataSeriesViewModel(label); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public DataSeries(String label, DataPoint[] dataPoints) { this.model = new DataSeriesViewModel(label, dataPoints); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public DataSeries(String label, Collection dataPoints) { this.model = new DataSeriesViewModel(label, dataPoints); this.model.addPropertyChangeListener(this); this.createComponents(); } /** * full constructor * @param model - the model */ public DataSeries(DataSeriesViewModel model) { this.model = model; this.model.addPropertyChangeListener(this); this.createComponents(); } /** * creates, binds and configures UI components. * data point properties can be created here as components or be painted in paintComponent. */ protected abstract void createComponents(); @Override public void propertyChange(PropertyChangeEvent evt) { this.repaint(); } /** * adds a data point to the series * @param dataPoint - the data point */ public void addDataPoint(DataPoint dataPoint) { this.model.addDataPoint(dataPoint); } /** * returns true if there is a data point with given category * @param category - the data point category * @return true if there is a data point with given category, otherwise false */ public boolean contains(String category) { return this.model.contains(category); } /** * returns the data point with given id or null if not found * @param uid - the id of the data point * @return the data point or null if there is no such point in the table */ public DataPoint getDataPoint(String category) { return this.model.getDataPoint(category); } /** * returns a collection of the data points. the collection supports removal, but does not support adding of data points. * @return a collection of data points */ public Collection getDataPoints() { return this.model.getDataPoints(); } /** * returns the label for the series * @return the label for the series */ public String getLabel() { return this.model.getLabel(); } /** * sets the max value * @param maxValue - the max value */ public Double getMaxValue() { return this.model.getMaxValue(); } /** * returns the number of data points in the series * @return the number of data points */ public int getDataPointCount() { return this.model.getSize(); } /** * returns an iterator over the data points * @return an iterator over the data points */ public Iterator iterator() { return this.model.iterator(); } /** * removes all data points from the series * @throws PropertyVetoException */ public void removeAll() { this.model.removeAll(); } /** * removes the data point with given id from the series, if present * @param category - the data point to remove */ public void removeDataPoint(String category) { this.model.removeDataPoint(category); } /** * returns the data series view model * @return - the data series view model */ public DataSeriesViewModel getViewModel() { return this.model; } /** * returns the data series model * @return - the data series model */ public DataSeriesModel getModel() { return this.model.getBean(); } } package at.onscreen.chart.builder; import java.util.Collection; import net.miginfocom.swing.MigLayout; import at.onscreen.chart.DataPoint; import at.onscreen.chart.DataSeries; import at.onscreen.chart.DataSeriesViewModel; public class BuilderDataSeries extends DataSeries { /** * default constructor */ public BuilderDataSeries() { super(); } /** * constructor * @param label - the series label */ public BuilderDataSeries(String label) { super(label); } /** * full constructor * @param label - the series label * @param dataPoints - an array of data points */ public BuilderDataSeries(String label, DataPoint[] dataPoints) { super(label, dataPoints); } /** * full constructor * @param label - the series label * @param dataPoints - a collection of data points */ public BuilderDataSeries(String label, Collection dataPoints) { super(label, dataPoints); } /** * full constructor * @param model - the model */ public BuilderDataSeries(DataSeriesViewModel model) { super(model); } @Override protected void createComponents() { this.setLayout(new MigLayout()); /* * * I want to add a new BuilderDataPoint for each data point in the model. * I want the BuilderDataPoints to be synchronized with the model. * e.g. when a data point is removed from the model, the BuilderDataPoint shall be removed * from the BuilderDataSeries * */ } } package at.onscreen.chart.builder; import javax.swing.JFormattedTextField; import javax.swing.JTextField; import at.onscreen.chart.DataPoint; import at.onscreen.chart.DataPointModel; import at.onscreen.chart.DataPointViewModel; import at.onscreen.chart.ValueFormat; import com.jgoodies.binding.adapter.BasicComponentFactory; import com.jgoodies.binding.beans.BeanAdapter; public class BuilderDataPoint extends DataPoint { /** * default constructor */ public BuilderDataPoint() { super(); } /** * constructor * @param category - the category */ public BuilderDataPoint(String category) { super(category); } /** * constructor * @param value - the value * @param label - the label * @param category - the category */ public BuilderDataPoint(Double value, String label, String category) { super(value, label, category); } /** * full constructor * @param model - the model */ public BuilderDataPoint(DataPointViewModel model) { super(model); } @Override protected void createComponents() { BeanAdapter beanAdapter = new BeanAdapter(this.getModel(), true); ValueFormat format = new ValueFormat(); JFormattedTextField value = BasicComponentFactory.createFormattedTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_VALUE), format); this.add(value, "w 80, growx, wrap"); JTextField label = BasicComponentFactory.createTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_LABEL)); this.add(label, "growx, wrap"); JTextField category = BasicComponentFactory.createTextField(beanAdapter.getValueModel(DataPointModel.PROPERTY_CATEGORY)); this.add(category, "growx, wrap"); } } To sum it up: I need to know how to bind a hash map property to JComponent.components property. JGoodies is in my opinion not very well documented, I spent a long time searching through the internet, but I did not find any solution to my problem. Hope you can help me.

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  • Database warehoue design: fact tables and dimension tables

    - by morpheous
    I am building a poor man's data warehouse using a RDBMS. I have identified the key 'attributes' to be recorded as: sex (true/false) demographic classification (A, B, C etc) place of birth date of birth weight (recorded daily): The fact that is being recorded My requirements are to be able to run 'OLAP' queries that allow me to: 'slice and dice' 'drill up/down' the data and generally, be able to view the data from different perspectives After reading up on this topic area, the general consensus seems to be that this is best implemented using dimension tables rather than normalized tables. Assuming that this assertion is true (i.e. the solution is best implemented using fact and dimension tables), I would like to see some help in the design of these tables. 'Natural' (or obvious) dimensions are: Date dimension Geographical location Which have hierarchical attributes. However, I am struggling with how to model the following fields: sex (true/false) demographic classification (A, B, C etc) The reason I am struggling with these fields is that: They have no obvious hierarchical attributes which will aid aggregation (AFAIA) - which suggest they should be in a fact table They are mostly static or very rarely change - which suggests they should be in a dimension table. Maybe the heuristic I am using above is too crude? I will give some examples on the type of analysis I would like to carryout on the data warehouse - hopefully that will clarify things further. I would like to aggregate and analyze the data by sex and demographic classification - e.g. answer questions like: How does male and female weights compare across different demographic classifications? Which demographic classification (male AND female), show the most increase in weight this quarter. etc. Can anyone clarify whether sex and demographic classification are part of the fact table, or whether they are (as I suspect) dimension tables.? Also assuming they are dimension tables, could someone elaborate on the table structures (i.e. the fields)? The 'obvious' schema: CREATE TABLE sex_type (is_male int); CREATE TABLE demographic_category (id int, name varchar(4)); may not be the correct one.

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  • django custom management command does not show up in production

    - by Tom Tom
    I wrote a custom management command for django. Locally with my dev settings everything works fine. Now I deployed my project onto the production server and the management command does not show up, respectively is not available. But I did not get an error message deploying the project (syncdb). Any ideas where I could try to begin to search? Is there a special command that all custom management commands are "autodiscovered"?

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  • how to make data that download from google-app-engine readable..

    - by zjm1126
    i use this to download all data from my google app: i follow this article: http://code.google.com/intl/en/appengine/docs/python/tools/uploadingdata.html#Creating_Exporter_Classes and download data use this: bulkloader.py --dump --url=http://zjm1126.appspot.com/remote_api --filename=b.csv but the data is : so how to make the data readable ? thanks

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  • Which open-source Scrum project management tool do you use?

    - by jumar
    I'm looking for an open-source Scrum project management tool for a small dev team (3 to 6 developers). I've been impressed by trac but I don't need its bug tracking feature as we already use Mantis. I'm having a look at iceScrum which seems feature-full and shiny but a bit cluttered. A solution that integrates into eclipse would be a plus.

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  • Role provider and Role management

    - by AspOnMyNet
    When the CacheRolesInCookie property is set to true in the Web.config file, role information for each user is stored in a cookie. When role management checks to see whether a user is in a particular role, the roles cookie is checked before the role provider is called to check the list of roles at the data source. The cookie is dynamically updated to cache the most recently validated role names. a) As far as I understand the above text, even though role management checks the roles cookie, role provider still checks the list of roles at the data source? b) Above text talks about role management, which is invoked before role provider is called. What class acts as a role management? thanx

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  • Specifying column names from a list in the data.frame command.

    - by MW Frost
    I have a list called cols with column names in it: cols <- c('Column1','Column2','Column3') I'd like to reproduce this command, but with a call to the list: data.frame(Column1=rnorm(10)) Here's what happens when I try it: > data.frame(cols[1]=rnorm(10)) Error: unexpected '=' in "data.frame(I(cols[1])=" The same thing happens if I wrap cols[1] in I() or eval(). How can I feed that item from the vector into the data.frame() command?

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  • What things must I know about OpenAL memory management?

    - by mystify
    I am playing sound with OpenAL, and it seems to increase memory footprint dramatically for every little sound I play. It seems that OpenAL never frees memory itself and that playing a Source causes memory footprint to grow. I couldn't find any good resources about OpenAL memory management, but I bet I must do a lot of stuff myself. Maybe someone knows a ressource for that?

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  • How do I view executed queries within SQL Server Management Studio?

    - by Brandon
    I am new to SQL Server Management Studio and am wondering if there is a way to see what queries have been ran against a database. Surely there is a way to see these. In the Activity monitor, there is a "Recent Expensive Queries" but I'm guessing that isn't all of the queries since I'm not seeing the ones I have ran. I am running SQL Server 2008 v 10.0.1600.22.

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  • How do i make form data not disappear after hitting refresh?

    - by acidzombie24
    I went to test my page on another browser. On google chrome i can fill out a form, hit back and forward and still have the data there. Now i need to refresh the page so certain data is correct (such as session id if the cookie expires or user logs out before submitting). I refresh and lose all data. Is there some option i can set so all data is kept?

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  • FairWarning Privacy Monitoring Solutions Rely on MySQL to Secure Patient Data

    - by Rebecca Hansen
    FairWarning® solutions have audited well over 120 billion events, each of which was processed and stored in a MySQL database. FairWarning is the world's leading supplier of privacy monitoring solutions for electronic health records, relied on by over 1,200 Hospitals and 5,000 Clinics to keep their patients' data safe. In January 2014, FairWarning was awarded the highest commendation in healthcare IT as the first ever Category Leader for Patient Privacy Monitoring in the "2013 Best in KLAS: Software & Services" report[1]. FairWarning has used MySQL as their solutions’ database from their start in 2005 to worldwide expansion and market leadership. FairWarning recently migrated their solutions from MyISAM to InnoDB and updated from MySQL 5.5 to 5.6. Following are some of benefits they’ve had as a result of those changes and reasons for their continued reliance on MySQL (from FairWarning MySQL Case Study). Scalability to Handle Terabytes of Data FairWarning's customers have a lot of data: On average, FairWarning customers receive over 700,000 events to be processed daily. Over 25% of their customers receive over 30 million events per day, which equates to over 1 billion events and nearly one terabyte (TB) of new data each month. Databases range in size from a few hundred GBs to 10+ TBs for enterprise deployments (data are rolled off after 13 months). Low or Zero Admin = Few DBAs "MySQL has not required a lot of administration. After it's been tuned, configured, and optimized for size on initial setup, we have very low administrative costs. I can scale and add more customers without adding DBAs. This has had a big, positive impact on our business.” - Chris Arnold, FairWarning Vice President of Product Management and Engineering. Performance Schema  As the size of FairWarning's customers has increased, so have their tables and data volumes. MySQL 5.6’ new maintenance and management features have helped FairWarning keep up. In particular, MySQL 5.6 performance schema’s low-level metrics have provided critical insight into how the system is performing and why. Support for Mutli-CPU Threads MySQL 5.6' support for multiple concurrent CPU threads, and FairWarning's custom data loader allow multiple files to load into a single table simultaneously vs. one at a time. As a result, their data load time has been reduced by 500%. MySQL Enterprise Hot Backup Because hospitals and clinics never stop, FairWarning solutions can’t either. FairWarning changed from using mysqldump to MySQL Enterprise Hot Backup, which has reduced downtime, restore time, and storage requirements. For many of their larger customers, restore time has decreased by 80%. MySQL Enterprise Edition and Product Roadmap Provide Complete Solution "MySQL's product roadmap fully addresses our needs. We like the fact that MySQL Enterprise Edition has everything included; there's no need to purchase separate modules."  - Chris Arnold Learn More>> FairWarning MySQL Case Study Why MySQL 5.6 is an Even Better Embedded Database for Your Products presentation Updating Your Products to MySQL 5.6, Best Practices for OEMs on-demand webinar (audio and / or slides + Q&A transcript) MyISAM to InnoDB – Why and How on-demand webinar (same stuff) Top 10 Reasons to Use MySQL as an Embedded Database white paper [1] 2013 Best in KLAS: Software & Services report, January, 2014. © 2014 KLAS Enterprises, LLC. All rights reserved.

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  • Partner Blog: Hub City Media Introduces iPad Application for Oracle Identity Analytics

    - by Tanu Sood
    About the Writer:Steve Giovannetti is CTO of Hub City Media, Inc., a company that specializes in implementation and product development on the Oracle Identity Management platform. Recently, Hub City Media announced the introduction of iPad application IdentityCert for Oracle Identity Analytics. This post explore the business use cases and application of IdentityCert.Hub City Media(HCM) has been deploying certification solutions based on Oracle Identity Analytics since it first appeared on the market as Vaau RBACx. With each deployment we've seen the same pattern repeat time and time again:1. Customers suffering under the weight of manual access certification regimens deploy Oracle Identity Analytics (OIA) for automated certification. 2. OIA improves the frequency, speed, accuracy, and participation of certifications across the organization. 3. Then the certifiers, typically managers and supervisors, ask, “Is there any easier way to do these certifications offline?”The current version of OIA has a way to export certification data to a spreadsheet.  For some customers, we've leveraged this feature and combined it with some of our own custom code to provide a solution based on spreadsheet exports and imports.  Customers export the certification to Microsoft Excel, complete it, and then import the spreadsheet to OIA. It worked well for offline certification, but if the user accidentally altered the format of the spreadsheet, the import of the data could fail. We were close to a solution but it wasn’t reliable.Over the past few years, we've seen the proliferation of Apple iOS devices, specifically the iPhone and iPad, in the enterprise.  As our customers were asking for offline certification, we noticed the same population of users traditionally responsible for access certification, were early adopters of the iPad. The environment seemed ideal for us to create an iPad application to support offline certifications using Oracle Identity Analytics. That’s why we created IdentityCert™.IdentityCert allows users to view their analytics dashboard, complete user certifications, and resolve policy violations with OIA, from their iPads.The current IdentityCert analytics dashboard displays the same charts that are available in the Oracle Identity Analytics product. However, we plan to expand the number of available analytics in future releases.The main function of IdentityCert is user certification which can be performed quickly and efficiently using a simple touch interface. Managers tap into a certification, use simple gestures to claim users and certify their access.  Certifications can be securely downloaded to IdentityCert and can be completed with or without a network connection. The user can upload the completed certifications once they are connected to a cellular or wi-fi network.Oracle Identity Analytics can generate policy violation notifications based on detective scans of identity warehouse or via preventative analysis of identity access requests. IdentityCert allows users to view all policy violations, resolve, or delegate them to appropriate users. IdentityCert also analyzes the policy violation expression and produces more human friendly descriptions of the policy violation which improves the ability of users to resolve the violation. IdentityCert can be deployed quickly into a customer's environment. It is deployed with Hub City Media's ID Services to connect Oracle Identity Analytics securely with the iPad application.Oracle Identity Management 11g R2 is an important evolutionary release. Oracle's Identity Management suite has more characteristics of a cohesive platform. This platform provides an integrated set of identity services that can be used to protect, manage, and audit security within the enterprise. At HCM we take the platform concept a step further and see it as an opportunity to create unique solutions for Oracle Identity Management customers. IdentityCert is our commitment to this platform. You can download IdentityCert from the Apple iOS App Store today. It includes a demo dataset that you can use to explore the functions of the product without any server infrastructure. Download it. Give it a try. We would appreciate your interest and welcome any feedback.Resources:Press Release: Hub City Media Introduces iPad Application IdentityCert™ for Oracle Identity AnalyticsApp Store Download: http://bit.ly/IdentityCertOracle Identity Governance Suite

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  • Indexing data from multiple tables with Oracle Text

    - by Roger Ford
    It's well known that Oracle Text indexes perform best when all the data to be indexed is combined into a single index. The query select * from mytable where contains (title, 'dog') 0 or contains (body, 'cat') 0 will tend to perform much worse than select * from mytable where contains (text, 'dog WITHIN title OR cat WITHIN body') 0 For this reason, Oracle Text provides the MULTI_COLUMN_DATASTORE which will combine data from multiple columns into a single index. Effectively, it constructs a "virtual document" at indexing time, which might look something like: <title>the big dog</title> <body>the ginger cat smiles</body> This virtual document can be indexed using either AUTO_SECTION_GROUP, or by explicitly defining sections for title and body, allowing the query as expressed above. Note that we've used a column called "text" - this might have been a dummy column added to the table simply to allow us to create an index on it - or we could created the index on either of the "real" columns - title or body. It should be noted that MULTI_COLUMN_DATASTORE doesn't automatically handle updates to columns used by it - if you create the index on the column text, but specify that columns title and body are to be indexed, you will need to arrange triggers such that the text column is updated whenever title or body are altered. That works fine for single tables. But what if we actually want to combine data from multiple tables? In that case there are two approaches which work well: Create a real table which contains a summary of the information, and create the index on that using the MULTI_COLUMN_DATASTORE. This is simple, and effective, but it does use a lot of disk space as the information to be indexed has to be duplicated. Create our own "virtual" documents using the USER_DATASTORE. The user datastore allows us to specify a PL/SQL procedure which will be used to fetch the data to be indexed, returned in a CLOB, or occasionally in a BLOB or VARCHAR2. This PL/SQL procedure is called once for each row in the table to be indexed, and is passed the ROWID value of the current row being indexed. The actual contents of the procedure is entirely up to the owner, but it is normal to fetch data from one or more columns from database tables. In both cases, we still need to take care of updates - making sure that we have all the triggers necessary to update the indexed column (and, in case 1, the summary table) whenever any of the data to be indexed gets changed. I've written full examples of both these techniques, as SQL scripts to be run in the SQL*Plus tool. You will need to run them as a user who has CTXAPP role and CREATE DIRECTORY privilege. Part of the data to be indexed is a Microsoft Word file called "1.doc". You should create this file in Word, preferably containing the single line of text: "test document". This file can be saved anywhere, but the SQL scripts need to be changed so that the "create or replace directory" command refers to the right location. In the example, I've used C:\doc. multi_table_indexing_1.sql : creates a summary table containing all the data, and uses multi_column_datastore Download link / View in browser multi_table_indexing_2.sql : creates "virtual" documents using a procedure as a user_datastore Download link / View in browser

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  • Oracle MDM Maturity Model

    - by David Butler
    A few weeks ago, I discussed the results of a survey conducted by Oracle’s Insight team. The survey was based on the data management maturity model that the Oracle Insight team has developed over the years as they analyzed customer IT organizations to help them get more out of everything they already have. I thought you might like to learn more about the maturity model itself. It can help you figure out where you stand when it comes to getting your organizations data management act together. The model covers maturity levels around five key areas: Profiling data sources; Defining a data strategy; Defining a data consolidation plan; Data maintenance; and Data utilization. Profile data sources: Profiling data sources involves taking an inventory of all data sources from across your IT landscape. Then evaluate the quality of the data in each source system. This enables the scoping of what data to collect into an MDM hub and what rules are needed to insure data harmonization across systems. Define data strategy: A data strategy requires an understanding of the data usage. Given data usage, various data governance requirements need to be developed. This includes data controls and security rules as well as data structure and usage policies. Define data consolidation strategy: Consolidation requires defining your operational data model. How integration is to be accomplished. Cross referencing common data attributes from multiple systems is needed. Synchronization policies also need to be developed. Data maintenance: The desired standardization needs to be defined, including what constitutes a ‘match’ once the data has been standardized. Cleansing rules are a part of this methodology. Data quality monitoring requirements also need to be defined. Utilize the data: What data gets published, and who consumes the data must be determined. How to get the right data to the right place in the right format given its intended use must be understood. Validating the data and insuring security rules are in place and enforced are crucial aspects for full no-risk data utilization. For each of the above data management areas, a maturity level needs to be assessed. Where your organization wants to be should also be identified using the same maturity levels. This results in a sound gap analysis your organization can use to create action plans to achieve the ultimate goals. Marginal is the lowest level. It is characterized by manually maintaining trusted sources; lacking or inconsistent, silo’d structures with limited integration, and gaps in automation. Stable is the next leg up the MDM maturity staircase. It is characterized by tactical MDM implementations that are limited in scope and target a specific division.  It includes limited data stewardship capabilities as well. Best Practice is a serious MDM maturity level characterized by process automation improvements. The scope is enterprise wide. It is a business solution that provides a single version of the truth, with closed-loop data quality capabilities. It is typically driven by an enterprise architecture group with both business and IT representation.   Transformational is the highest MDM maturity level. At this level, MDM is quantitatively managed. It is integrated with Business Intelligence, SOA, and BPM. MDM is leveraged in business process orchestration. Take an inventory using this MDM Maturity Model and see where you are in your journey to full MDM maturity with all the business benefits that accrue to organizations who have mastered their data for the benefit of all operational applications, business processes, and analytical systems. To learn more, Trevor Naidoo and I have written the Oracle MDM Maturity Model whitepaper. It’s free, so go ahead and download it and use it as you see fit.

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