DATA MANAGEMENT INSIGHTS
Turn big data into big value
Recent Data Management articles
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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How does one of the largest cities in the world use data for social good? From data privacy to data quality, what are the challenges in using data for social good, and how does one large organization in New York City address them? Hear from a research scientist at the Center for Innovation through Data Intelligence about the data they have, the questions they ask of it, and the data they’d like to see in the future.
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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.
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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.
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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.
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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.
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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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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.
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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?
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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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Goooooal! How data stewards score with data visualizationWhen it comes to data visualization, the role a data steward plays is not so different from that of a referee. They both enforce rules, stay true to the game -- and are critical to success.
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Understanding data in motionLearn how to analyze fast moving data streams on the fly with event stream processing.
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Charlie Brown's Teacher Speaks Hadoop. Do you?Ever felt like you and your big data specialist were speaking different languages? Learn how a non-geek can speak big data.
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Canada Post on the (careful) commercialization of dataAs a common data point across databases, address data is an integral part to any master data management strategy. It’s powerful when it’s right; frustrating when it’s not. Could Canada Post turn a seemingly ordinary data point into a profitable business line?
Data Management: The Basics
Data Management
Data management can often mean the difference between a business that will succeed and one that will drown in too much disorganized information. With high-quality, well-managed data, you can gain a clearer picture of your business. Access the right data when you need it. And make better, more strategic decisions.
From data quality to data integration to master data management, data management solutions help you stop reacting to bad data – and start using your data to make a difference.
What is big data?
For most organizations, big data is the reality of doing business. It’s the proliferation of structured and unstructured data that floods your organization on a daily basis – and if managed well, it can deliver powerful insights.
Imagine being able to analyze data to determine the root cause of failures. Or detect fraudulent behavior before it affects revenue. Implementing the right solutions to make the most of your big data – from data management to analytics – can be key to your business success.
SAS & Hadoop
Organizations with massive volumes of data are turning to Hadoop to extract value from all that information. But what is Hadoop, exactly – and how can it help your organization? Learn how Hadoop is evolving to meet the big data challenges of today and tomorrow. And how you can take advantage of data management, data visualization and analytics to get faster, more meaningful insights from your Hadoop environment.
ETL (extract, transform, load)
Older technologies don't always die out and get replaced with newer technologies. Sometimes they adapt to the times and retain their relevance. That’s what has happened with ETL (extract, transform, load) – a decades-old technology that many organizations still rely on as part of their larger data integration strategy. Learn the history of ETL and how it works, then find out where it fits in a world of big data, Hadoop and streaming.
What is a data warehouse?
With large amounts of data readily available to organizations, the question is no longer how businesses collect it – but how they store it. Data warehouses are a reliable solution. They serve as a repository for data that's been collected and integrated from multiple sources. And unlike data lakes, which store raw data, data warehouses contain data that's consistently formatted so it's ready for analytics or reporting purposes.
Blockchain
What can you store in blockchain besides Bitcoin transactions? Insurance claims, medical records and even voting records can all be stored in blockchain. Simply put, blockchain is a distributed data architecture that stores data and transactions – and validates the accuracy of those transactions by consensus. Learn more about blockchain and how you can analyze blockchain data.
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