DATA MANAGEMENT INSIGHTS
Turn big data into big value
Recent Data Management articles
- Key questions to kick off your data analytics projectsThere’s no single blueprint for starting a data analytics project. Technology expert Phil Simon suggests considering these ten questions as a preliminary guide.
- The five D's of data preparationFrom discovering which data is best to use, to delivering it in the right format to users, learn why these 5 D’s are essential to data preparation.
- How do free-to-play video games earn big profits?How does the industry leader of free-to-play, massively multiplayer online games scale its customer intelligence and analytics efforts to thousands of models and terabytes of data a day? With industrialized modeling from SAS.
- Data quality management What you need to knowData quality isn’t simply good or bad. Data quality management puts quality in context to improve fitness of the data you use for analysis and decision-making.
- The future of IoT: On the edgeFrom cows to factory floors, the IoT promises intriguing opportunities for business. Find out how three experts envision the future of IoT.
- Data lake and data warehouse – know the differenceData lake – is it just marketing hype or a new name for a data warehouse? Find out what a data lake is, how it works and when you might need one.
- What is data profiling and how does it make big data easier?Data profiling, the act of monitoring and cleansing data, is an important tool organizations can use to make better data decisions.
- 5 steps to sustainable GDPR complianceFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
- General Data Protection Regulation: From burden to opportunityThe General Data Protection Regulation stirs up mixed emotions, but Kalliopi Spyridaki shows how to use the new legislation for business advantage.
- The importance of data quality: A sustainable approachBad data wrecks countless business ventures. Here’s a data quality plan to help you get it right.
- Data governance: The case for self-validationLearn why you should redefine data governance policies to empower customers to be accountable for keeping their personal data accurate, consistent and up-to-date.
- What was your data doing during the financial crisis?Financial institutions usually survive a crisis, then react to prevent it in the future. SAS' Mazhar LeGhari explains how data can help you break that cycle.
- Hadoop is the new boardroom buzzwordIn this Q&A, two Hadoop experts share what every executive needs to know.
- Data governance framework: What is it and do I already have one?A data governance framework encompasses a holistic approach to how you collect, manage and archive data.
- Soccer versus baseball: which is the best analogy for data governance?Is data governance more like baseball, featuring individual effort, or like soccer, where a team approach wins? Carol Newcomb evaluates the best sports analogy for data governance.
- Data quality: The Achilles' heel of risk managementGiven the tightly regulated environment banks face today, the importance of data quality cannot be overstated. Beyond the obvious benefits of staying one step ahead of regulatory mandates, having accurate, integrated and transparent data will drive confident, proactive decisions to support a solid risk management foundation.
- A Getting Started With Hadoop ChecklistFrom low-cost storage to distributed processing, Hadoop offers many promises. But there’s an expanding analytics ecosystem evolving around this big data platform that’s worth some study. Read our checklist and make sure you’re not overlooking anything important in your rush to get value from Hadoop.
- You don’t know me. Or do you? Data meets anthropologyLaw and medicine. Anthropology and data management. And so on. What new advances can happen when fields of study converge?
- Components of an information management strategyBefore starting a data management strategy for your business, you need to understand each component. Data expert David Loshin breaks them down.
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