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The Difference Between Data Architecture and Enterprise Architecture

erwin

Whereas a data architect’s scope, is mostly limited to the “What”(data), and from a system model/logical (level 3) perspective. The Value of Data Architecture. We’re working in a fast-paced digital economy in which data is extremely valuable. Good data leads to better understanding and ultimately better decision-making.

Sales 131
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Artificial Intelligence: 6 Step Solution Decomposition Process

Bill Schmarzo - Dell EMC

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? Bounty of potential data sources to be mined for actionable insights in support of the business initiative. Figure 8: Data Lake Components.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Your skill set should include the ability to write in the programming languages Python, SAS, R and Scala.

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How to Take Your Business to The Next Level with Data Intelligence

erwin

Transforming Industries with Data Intelligence. Data intelligence has provided useful and insightful information to numerous markets and industries. With tools such as Artificial Intelligence, Machine Learning, and Data Mining, businesses and organizations can collate and analyze large amounts of data reliably and more efficiently.

Analytics 103
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#InfoGov Links Of The Week 02-17-2017

Information is Currency

The Conflict between Data Science and Cybersecurity. Cybersecurity is in direct conflict with the basis tenants of data analysis, especially big data analysis, predictive analytics and data mining. Big Data: Why Should You Be Aware of It. 5 ECM Lessons from a Non Verbal Communication Expert.

MDM 40
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ManagePlus—your journey before, with and beyond RISE with SAP

IBM Big Data Hub

Enabling true transformation You’re on the lookout for adoption of industry best practices along with the capabilities of process mining and process discovery to both simplify and standardize the process flows. From a business and IT perspective, this helps in cycle time and eventually price per business object.

Cloud 87
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How data, AI and automation can transform the enterprise

IBM Big Data Hub

For line-of-business functions, here are five key capabilities to consider: Process mining to identify the best candidates for automation and scale your automation initiatives before investments are carried out. The challenge is bringing it all together and implementing it across lines of business and IT.