DATA MANAGEMENT INSIGHTS
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Recent Data Management articles
- IoT: The customer experience accelerator you can't afford to ignoreIoT represents a powerful source of data that, when combined with analytics, can yield insights on everything from behavior to emotions to health. And that's why it's key to improving customer experience.
- Data lineage: Making artificial intelligence smarterFor AI to reach its full potential, the data feeding its algorithms and models needs to be well-understood. Data lineage plays a vital role in understanding data, making it a foundational principle of AI.
- 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.
- Data management backgrounderFrom data integration to data quality and data preparation, find out what these terms mean and why they’re so important for your analytics projects.
- 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.
- Three C’s of the connected customer in the IoTTo optimize the connected customer experience, Blue Hill Research says organizations should build an IoT model based on three key features.
- IoT success depends on data governance, security and privacyThe IoT puts intense demands on the data management life cycle. Learn from 10 common mistakes organizations have made with IoT endeavors.
- Data management for cybersecurity: Know the essentialsSecurity teams tend to underestimate the importance of data management for cybersecurity. See the seven key reasons data management has been so difficult and five steps to getting it right.
- 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.
- 5 data management best practices to help you do data rightFollow these 5 data management best practices to make sure your business data gives you great results from analytics.
- 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.
- 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.
- People, process, culture – and technologyData governance requires measurement and constant improvements of data quality. That’s a mountain of a job without clearly defined roles and responsibilities. Peyman Mestchian, Managing Partner at Chartis Research, and Tom Kimner, Head of Americas Risk at SAS, talk about data governance and the need for specialized departments, technology and skills.
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