Manage your data as a valuable resource
Data may be your most valuable resource. It's certainly not an endangered one. It pours into organizations from every conceivable source – operational and transactional systems; scanners, sensors and smart meters; inbound and outbound customer contact points; mobile media and the Web.
But what makes data valuable? Its source? Its quantity? Its format? No, the value of data depends on what you do with it. And the first step in unlocking its potential lies in data management. So what do you know about data management? What do you need to know? Browse around and see what the experts are saying about data management.
Is your data easy to access, clean, integrate and store? Do you know which types of data are used by everyone in the organization? And do you have a system in place for analyzing data as it flows into the organization? Brush up on the concepts below to start your data management journey:
- Data access refers to your ability to get to and retrieve information wherever it is stored. Certain technologies can make this step as easy and efficient as possible so you can spend more time using the data – not just trying to find it.
- Data quality is the practice of making sure data is accurate and usable for its intended purpose. This starts from the moment data is accessed and continues through various integration points with other data – and even includes the point before it is published or reported.
- Data integration defines the steps for combining different types of data. Data integration tools help you design and automate the steps that do this work.
- Data federation is a special kind of virtual data integration that allows you to look at combined data from multiple sources without the need to move and store the combined view in a new location.
- Data governance is an ongoing set of rules and decisions for managing your organization’s data to ensure that your data strategy is aligned with your business strategy.
- Master data management (MDM) defines, unifies and manages all of the data that is common and essential to all areas of an organization. This master data is typically managed from a single location or hub.
- Data streaming involves analyzing data as it moves by applying logic to the data, recognizing patterns in the data and filtering it for multiple uses as it flows into your organization.
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More on data management
What's the big deal about data management?
If your analytics projects aren’t successful, it might be a data management problem. Watch this video to learn how data management can help improve and control data for all your analytics projects.
Consider this: 30 percent of companies say they have no strategy for managing big data – but they need one.
Learn more in the Managing Big Data report from TDWI
The data-driven company
It is essential that we can convert what is purely data and information into knowledge and intelligence.
Head of Government Management, CSI Piemonte
If your data management efforts are successful, then the operational and analytical systems that drive the business will be more successful. According to an IDG Research Services study, the top five reasons for deploying data management solutions include:
- Reducing costs and increasing operational efficiencies.
- Improving agility.
- Improving existing business processes.
- Improving decision making.
- Increasing IT alignment with the business.
Data management in the digital economy
Are you managing your data for yesterday’s industrial economy or for the new digital economy?
What’s the difference? Well, are you still sorting and storing everything into data warehouses? Or does your IT infrastructure also take advantage of streaming data and external data sources from mobile devices and the Web?
In the big data world, the concept of data management is evolving, and your systems need to evolve to keep up.
Traditional methods for data governance and master data management are still important, but new practices for event stream processing and open source storage cannot be overlooked.
Learn how organizations of all sizes are integrating Hadoop into their existing IT architectures – and how their analytics are improving as a result.