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Data Modeling Trends in 2019

IT technologies are rapidly changing our lives. Whether it’s your daily grocery purchase, monthly bill payments, booking railway tickets, or receiving online healthcare consultation, data technologies have penetrated every business model, large, medium, or small. Recent cloud platforms, coupled with Big Data and IoT technologies, have ushered in a new era of “smart technologies” powered […]

2019: Full Scale Schema Modeling

Click to learn more about author Thomas Frisendal. Using Concerns to Navigate Data Architectures Welcome to 2019! This is the year that offers us a unique opportunity to re-architect the way we think schemas, data models and Data Architecture. We do indeed need to do some things better. The real world is full of concerns, […]

Data Architecture with Data Governance: A Proactive Approach

“Data Architecture is the physical implementation of the Business Strategy,” said Nigel Turner, Principal Consultant in E.M.E.A. at Global Data Strategy, Ltd., speaking at the DATAVERSITY® Enterprise Data Governance Online Conference. “It’s a key part of the whole continuum that you need to build within an organization to manage data effectively,” and Data Governance forms […]

Ten Myths About Data Science

Click to learn more about author Daniel Jebaraj. Introduction Data Science is now being used as a competitive weapon. As with other technologies and processes that can transform the way companies operate, there’s a lot of contradictory information about it that’s causing considerable confusion. Most of today’s business leaders have heard that Data Science can […]

Solving Knowledge Graph Data Prep with Standards

Click to learn more about author Dr. Jans Aasman. There’s a general consensus throughout the data ecosystem that Data Preparation is the most substantial barrier to capitalizing on data-driven processes. Whether organizations are embarking on Data Science initiatives or simply feeding any assortment of enterprise applications, the cleansing, classifying, mapping, modeling, transforming, and integrating of data […]

Why Data Science is Not Statistics

Click to learn more about author Alex Paretski. Statistics as a branch of applied mathematics plays an important role in identifying hidden patterns in data. That’s why it is frequently used interchangeably with broader terms such as Data Science, Data Analytics, Business Analytics, and Machine Learning. Not only is this comparison technically incorrect, but it […]

Data Modeling vs. Data Architecture

In the second edition of the Data Management Book of Knowledge (DMBOK 2): “Data Architecture defines the blueprint for managing data assets by aligning with organizational strategy to establish strategic data requirements and designs to meet these requirements.” Another way to look at it, according to Donna Burbank, Managing Director at Global Data Strategy: “Data […]

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