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 these 10 questions as a guide.
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Data lake : Présentation et atoutsUn data lake est un type de référentiel de stockage qui ingère rapidement de grandes quantités de données brutes et hétérogènes dans leur format natif. Les data lakes contiennent tout type de données, de plusieurs sources en un seul référentiel et permettent un accès, une exploration et une visualisation en libre-service. Les entreprises peuvent ainsi voir et réagir plus rapidement à de nouvelles informations.
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Public health infrastructure desperately needs modernizationPublic health agencies must flex to longitudinal health crises and acute emergencies – from natural disasters like hurricanes to events like a pandemic. To be prepared, public health infrastructure must be modernized to support connectivity, real-time data exchanges, analytics and visualization.
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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.
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The transformational power of evidence-based decision making in health policyState health agencies are under pressure to deliver better health outcomes while minimizing costs. Read how data and analytics are being used to confront our biggest health care challenges head on.
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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.
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Data lineage: Making artificial intelligence smarterLear how data lineage plays a vital role in understanding data, making it a foundational principle of AI.
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What big data has brought to the privacy discussionHow does big data impact your privacy? There are ways to balance privacy and security in an increasingly transparent and dangerous world.
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Bringing data to the streamHow much do we know about fresh water systems and the dynamic nature of streams and rivers? Find out how one data scientist turned his fascination with streams and rivers into a career.
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GDPR and AI: Friends, foes or something in between?The GDPR may not be best buddies with artificial intelligence – but GDPR and AI aren't enemies, either. Kalliopi Spyridaki explains the tricky relationship between the two.
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Personal data: Getting it right with GDPRTo learn more about the definition of personal data, why it’s in the news and why it’s being tightly regulated by laws like the General Data Protection Regulation (GDPR), we interviewed Jay Exum, Privacy Counsel at SAS.
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Data integration: It ain't what it used to beOnce limited in scope, data integration now supports analytics and data-driven operational processes like real-time insurance claims processing and IoT apps.
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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.
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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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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.
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Cinq étapes pour une conformité durable à GDPRFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
Data Management: The Basics
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 digital transformation?
Definitions of digital transformation vary. But no matter how it’s defined, the competitive advantage that results is accomplished when an organization effectively uses digital technology to dramatically streamline and improve processes, customer service and business operations. Formed at the intersection of people, business and technology, digital transformation affects many aspects of our lives – how we work, shop, travel, educate, govern and live. Today we feel its effect across all industries, large and small alike.
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.
What is 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.
What is 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.
What is cloud computing?
Cloud computing provides access to easily scalable computational resources for software and data storage by eliminating the need for storage on local systems and infrastructure. Services and data can be securely accessed as needed to extend capabilities or reduce costs.
What is 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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