A Single Point of Control for Enterprise
Data Management
Organizations today are faced with a daunting challenge – how to control the information that serves as the very foundation of their business success. However, with the recent, exponential growth in data and the proliferation of siloed, disparate data, organizations are realizing that the data that is fundamental to their success doesn’t meet their needs.
DataFlux Data Management Studio provides a single interface for both business and IT users to plan, implement and monitor the rules to manage data throughout the organization. Part of the DataFlux Data Management Platform, Data Management Studio provides a unified development and delivery
environment, giving organizations a single interface to analyze, improve and control data and drive enterprise data management.
By delivering a single, accurate and consistent view of any and all DataFlux tasks through a user-friendly process and technology framework, Data Management Studio lets you:
• Enable both business and IT users with increased control of data management tasks
• Enhance cross-functional data governance through a single place to create, optimize and manage business rules
• Profile, monitor and actively manage the quality of enterprise data
• Provide a consistent user experience for all phases of data management
Data Management at Your Fingertips
Data Management Studio offers a unique set of workflow tools built on an industry-leading
technology platform that encompasses every facet of the data management process. Through its intuitive interface, Data Management Studio provides business and IT users with powerful data improvement
capabilities and control over data management and data governance initiatives.
Data Management Studio provides the ability to design and manage processes to:
• Merge customer, product or other enterprise data • Unify disparate data through a variety of data
integration methods (batch, real-time, virtual) • Verify and validate customer and product
information
• Integrate disparate data sets, with an eye on quality • Transform and standardize various data entities • Monitor data for compliance and data quality
control
• Manage metadata hierarchies
By enabling consistent, accurate and timely data throughout the enterprise, Data Management Studio gives organizations the ability to implement the people, process and technology changes necessary to establish an effective data governance strategy. Data
Management Studio provides powerful functionality to meet today’s demanding data management challenges.
DataFlux Data Management Studio
A collaborative design environment allows business and IT users to develop and refine data jobs and services.
Data Quality
Standardize, rationalize and transform corporate information
Better data leads to better decisions which, ultimately, lead to better business. Data Management Studio gives both business and IT users the full capabilities of the DataFlux industry-leading data quality technology. Through patented matching technology, transformation routines and identification logic, DataFlux helps you easily correct data problems for virtually any and all types of enterprise data.
DataFlux Data Management Studio allows you to: • Plan and prioritize data correction initiatives • Identify and resolve problematic data
• Normalize and transform data according to both pre-built and custom data quality rules • Validate data and improve overall accuracy
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Data profiling provides immediate feedback on the accuracy and integrity of data sources.
Data Profiling
Discover data characteristics to guide data quality and data integration efforts
Data Management Studio provides industry-leading data profiling capabilities, providing insight into the health of the data. Data profiling is critical when you need to identify the root cause of poor-quality and disparate data sources. Through a data discovery program, Data Management Studio helps you gain the knowledge to design effective data quality, data integration and master data management (MDM) business rules to support your organization’s data-driven initiatives.
Data profiling provides an in-depth assessment of your organization’s data, examining the structure, completeness and suitability of your data assets. Data Management Studio lets you:
• Develop a comprehensive assessment of the scope and nature of data quality issues • Create an inventory of data assets
Data Integration
Intelligently match, merge and consolidate data
An effective data integration strategy can lower costs and improve productivity by enabling consistent, accurate and reliable data across your enterprise. Data Management Studio provides users with a single interface for data quality and data integration activities, including the design, navigation and management of data integration jobs and workflows. These rules can then be executed via the DataFlux Data Management Server for real-time or batch processing as well as the DataFlux Federation Server for virtual data integration capabilities.
Data integration involves combining processes and technology to enable your enterprise to make the most effective use of disparate, inconsistent data. Data Management Studio allows you to build rules that can support:
• ETL and ELT – Extract, transform and load data from multiple sources, using both traditional batch processing and in-database methods
• Data migration – Transfer data to new locations while improving the accuracy and consistency of data during the migration project
• Real-time data integration – Match information within or across data sources and provide instant access to reliable data from across the IT infrastructure
Metadata Analysis
Extract, organize and analyze metadata anywhere in the enterprise
Metadata analysis uncovers existing trends and characteristics of your data, examining corporate data throughout your enterprise and providing a clear picture of the types and sources of that data. This understanding is an essential first step to any enterprise data management initiative.
Data Management Studio provides the ability to discover and manage metadata from virtually any data source – anywhere in the organization – from a single interface.
• Organize data logically across all data sources • Simplify projects by accurately grouping related data
• Gain insight into the data that should be included in a data management project
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Entity Resolution
Match data and identify potential data relationships across sources
The ability to link and consolidate entity information with a high level of confidence is critical to data management initiatives. Information about the same customer, product or employee may exist in multiple databases, in many unique forms. The challenge is to find and resolve similar records in different data sources. Data Management Studio offers industry-leading matching technology that enables accurate entity
resolution across multiple data sources. With this technology, you can:
• Identify individuals across multiple data sources from incomplete and non-obvious relationships • Intelligently manage entity resolution routines through advanced fuzzy-matching technology • Create multi-record clusters, confidence scores and scatter plots to determine potential clusters • Analyze the suitability of data elements as potential identifying attributes
• Recognize when slight variations suggest a connection between records
The DataFlux Data Management Methodology is a step-by-step process for performing data management tasks, such as data quality, data integration, data migrations and MDM. When organizations plan, take action on and monitor data management projects, they build the foundation to optimize revenue, control costs and mitigate risks.
No matter what type of data you manage, DataFlux technology can help you gain a more complete view of corporate information.
DataFlux Data Management Methodology
Defi ne
The planning stage of any data management projects starts with this essential fi rst step. This is where the people, processes, technologies and data sources are defi ned. Roadmaps are built that include articulating the acceptable outcomes. Finally, the cross-functional teams across business units and between business and IT communities are created to defi ne the data management business rules.
Execute
Once business users have established how the data and rules should be defi ned, the IT staff can install them within the IT infrastructure and determine the integration method – real-time, batch or virtual. These business rules can be reused and redeployed across applications, helping increase data
consistency in the enterprise.
Discover
A quick inspection of your corporate data would probably fi nd that it resides in many different
databases, managed by many different systems, with many different formats and representations of the same data. This step of the methodology lets you explore metadata to verify that the right data sources are included in the data management program – and create detailed data profi les of identifi ed data sources to understand their strengths and weaknesses.
Evaluate
This step of the methodology allows users to defi ne and enforce business rules to measure the
consistency, accuracy and reliability of new data as it enters the enterprise. Reports and dashboards on critical data metrics are created for business and IT staff members. The information gained from data monitoring reports is used to refi ne and adjust the business rules.
Design
After completing the fi rst two steps, this phase allows you to take the different structures, formats, data sources and data feeds, and create an environment that accommodates the needs of your business. At this step, business and IT users build workfl ows to enforce business rules for data quality and data integration, and create data models to house data in consolidated or master data sources.
Control
The fi nal stage in a data management project involves examining any trends to validate the extended use and retention of the data. Data that is no longer useful is retired. The project’s success can then be shared throughout the organization. The next steps are communicated to the data management team to lay the groundwork for future data management efforts.
Data Enrichment
Transform incomplete data into useable, standardized information
Data Management Studio enables data verifi cation and standardization – key components in data
quality projects that contain customer, supplier, company or employee data elements. Data Management Studio gives you the ability to create complete and accurate address information for more than 240 countries around the world. In addition, DataFlux can enrich address data with geographic, demographic or other details, as well as standardize and augment data on products, materials and services.
Through industry-leading matching and standardization technology that automatically inspects every element of a record, Data Management Studio verifi es its integrity and corrects invalid information to meet defi ned requirements. DataFlux technology enables you to:
• Reconcile, cleanse and enrich internal address data
• Create accurate reports and analytics on customers, both internally and for compliance requirements • Substantially reduce undeliverable mail and reduce associated costs
• Add value to data on materials, products and services
Data Monitoring
Enforce business rules and build the foundation for data governance
By creating business rules once and reusing them across applications, you can apply a uniform set of business standards in real time across any system. Data Management Studio provides the design, development and monitoring environment for proactive data governance, so you can:
• Design and enforce rules to determine if data is maintained within proper control limits and meets pre-defi ned business rules
• Create data alerts and controls to verify that data remains in compliance with internal and external data policies
• React to data problems quickly, before the inaccurate or invalid data negatively impacts the business • Create customized business rules to validate and audit operational processes
• Enable enterprise governance, risk and compliance monitoring
DataFlux data monitoring technology uses an advanced service-oriented architecture (SOA) to expose data monitoring rules as web services to enable ongoing, accurate information. These rules can operate within your existing IT framework, providing regular status checks of data governance procedures.
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