DATA MANAGEMENT INSIGHTS
Trasforma i big data in informazioni di valore
Articoli e altre risorse sul Data Management
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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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What is a data lake & why does it matter?As containers for multiple collections of data in one convenient location, data lakes allow for self-service access, exploration and visualization. In turn, businesses can see and respond to new information faster.
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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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Recommendation systemsCome fanno i recommendation system a sapere cosa stai cercando mentre stai facendo shopping online?
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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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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.
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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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5 steps to sustainable GDPR complianceFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
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How openness can supercharge event stream analyticsWhat does openness do for event stream analytics? David Loshin shows how it helps you speed and govern the full streaming analytics life cycle.
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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.
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Big data privacy: Four ways your data governance strategy affects security, privacy and trustWith IT and business strategies converging, something that’s a little late to the party is the concept of big data privacy.
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How to improve data prep for analytics: TDWI shares best practicesGetting good results from your data means doing a good job of preparing the data for analytics. Find out what TDWI says it takes to get there.
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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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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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Streaming data: The ins and outs of this technology buzzwordLearn what streaming data is, why it matters to your business and how it relates to big data, event stream processing, data management and the IoT.
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The scoop on HadoopCloudera co-founder Mike Olson talks trends, changes and outlines the formula for success with Hadoop.
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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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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 not as easy as it sounds, especially in a big data age.
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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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Sensing a disturbance in the dataAs IoT data unites with event stream processing (ESP), these combined forces will automatically sense data pattern deviations and trigger immediate response.
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Hadoop survey results reveal use cases, needs and trendsHow are companies using Hadoop? Why are adoption rates still low? And why is it so important? Data professionals’ candid answers may surprise you.
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The “problem-solver” approach to data preparationNoted technology author David Loshin explains why it's important to know what the problems are before getting data ready for analytics.
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.
Data Management: che cos'è
- Panoramica
- Digital Transformation
- Cosa sono i big data?
- SAS e Hadoop
- Che cos'è l'ETL?
- Che cos'è un data warehouse?
- Cloud Computing
- Blockchain
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.
Cosa sono i big data?
Per molte organizzazioni, i big data sono la vera realtà di chi fa business. Sono i dati, strutturati e non, che ogni giorno si diffondono nella tua azienda - e se vengono maneggiati sapientemente, possono fornire informazioni potenti e indispensabili.
Immagina di essere in grado di analizzare i dati per determinare le cause alla base di un guasto. O di poter rilevare atteggiamenti fraudolenti prima che influiscano sul fatturato. Per ottenere il massimo del valore dai tuoi dati, la chiave del tuo successo aziendale potrebbe essere applicare le soluzioni giuste, dal data management agli analytics.
SAS e Hadoop
Le organizzazioni con enormi volumi di dati si stanno convertendo ad Hadoop per estrarre valore da tutte quelle informazioni. Ma cos'è esattamente Hadoop - e come può aiutare la tua organizzazione? Scopri come Hadoop si sta evolvendo per affrontare le sfide dei big data nel presente e nel futuro. E come puoi sfruttare strumenti come data management, data visualization e analytics, per ottenere velocemente le informazioni indispensabili dal tuo ambiente Hadoop.
ETL (extract, transform, load)
Le vecchie tecnologie non sempre vengono soppiantate dalle nuove. Qualche volta sono in gradi di adattersi ai tempi e mantenere la loro importanza. Un esempio in questo senso è l'ETL (extract, transform, load) una tecnologia pluridecennale su cui molte aziende fanno ancora affidamento per la propria strategia di data integration. Scopri la stroria dell'ETL, come funziona, e qual'è il suo ruolo nel mondo dei big data, di Hadoop e streaming.
Che cos'è un data warehouse?
Con un'enorme quantità di dati disponibili per le aziende, la domanda non è più come acquisirli, ma come archiviarli. I data warehouses sono una soluzione affidabile. Funzionano come repository per tutti quei dati raccolti e integrati da sorgenti multiple. E al contrario dei data lakes, che archiviano dati grezzi, i data warehouse contengono dati formattati appositamente per l'analisi o per il reporting.
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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