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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5 ways data monetization can inform data strategyData monetization promises more than monetary returns. Anne Buff explains how monetization drives strategy for data-driven organizations.
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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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Tips for successful data integration modernizationOrganizations today have to capture, process and move all types of new and big data. Get some tips for data integration modernization from TDWI.
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Coming soon: The Industrial Internet and IoT standardsFrom smart farms to connected water meters, the IIoT party is happening – with consensus around IoT standards playing host.
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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.
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Chief data officer role shakes up traditional data governanceDoes every organization need someone in the chief data officer role to manage data governance?
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8 ways an enterprise data strategy enables big data analyticsAnalyzing big data can reveal new insights and strengthen business decisions. Here's why you need an enterprise data strategy to help you get there.
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Big data management: 5 things you need to knowBig data management demands new tools and processes. Learn about 5 things that can help you manage big data better and get consistent analytic results.
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Clear-cut big data strategy tied to strong financial performanceWondering how important your big data strategy is? Find out from this 2015 report that’s based on a survey of more than 500 global executives.
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An analytics checklist for customer intelligenceYou use checklists to help you perform crucial tasks every day. Why not use this checklist to help guide you in building the best customer intelligence in your industry?
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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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3 things you need to know about event stream processingAs more data is generated from the Internet of Things, more of it will be analyzed as it is streaming. Learn how to analyze streaming data – and how it differs from traditional analysis.
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Big data integration: Go beyond 'just add data'Every business-focused technology requires users to "just add data." This article by Matt Magne explores why that's much easier than it sounds, especially in a big data age.
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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 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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