White Papers, Research Papers, and eBooks

Data Virtualization for Dummies: Learn How to put Data Virtualization to Work in your Organization

With the advent of big data and the proliferation of multiple information channels, organizations must store, discover, access, and share massive volumes of traditional and new data sources. View Now

Data Enablement: Building a Foundation of Trust and Governance in the Data-Driven Era

Download our research and learn how you can build a rock-solid foundation—hint: it starts with data quality—for an exceptional customer experience. View Now

Why Data and Data Governance Matter More Than Ever: Leading the Charge for Regulatory Compliance

Trust for brands is more important than ever, and nowhere is that more critical today than in how brands use consumer data. Witness the current state of data privacy and regulations, such as the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). View Now

For Better Self-Service Analytics, Turn to Smart Catalogs

Self-service analytics is increasingly important for enterprise competitiveness. A company’s business users won’t be able to perform self-service analytics effectively unless they can count on access to trusted and appropriate data sources. View Now

Data Strategy: Getting from Defense to Offense – A User’s Guide

Arrayo spoke with industry executives and experts about the keys to success in data governance. We talked to Chief Data Officers, Chief Digital Officers, Chief Financial Officers, and experts in finance, pharma, biotech and healthcare. View Now

An Introduction to Machine Learning Interpretability

Understanding and trusting models and their results is a hallmark of good science. Analysts, engineers, physicians, researchers, scientists, and humans in general have the need to understand and trust models and modeling results that affect our work and our lives. View Now

The Automated Business Glossary: Everything You Need to Know

Whether you’re on the business side of your organization or the IT side, you know that a Business Glossary is key to speaking a common data language.  Problem is, building a Business Glossary is a HUGE pain in the…, errr, a huge project that no one wants to take on. View Now

Trends in Data Management: A 2019 DATAVERSITY Report

DATAVERSITY® asked what’s happening in Data Management through a 2019 Trends in Data Management survey. This paper details and analyzes the latest thoughts, trends, and activities indicated by those who participated in the study. View Now

What is… ?

What is Data Management? What is Data Governance? What is Metadata? Get the short answers to these and nine more hot data topics. View Now

Trends in Data Governance and Data Stewardship

The foundation of this report is a survey conducted by DATAVERSITY® that included a range of different question types and topics on the current state of Data Governance and Data Stewardship. View Now

Trends in Data Architecture

The foundation of this report is a survey conducted by DATAVERSITY® that included a range of different question types and topics on the current state of Data Architecture. The report evaluates the topic through a discussion and analysis of each presented survey question, as well as a deeper examination of the present and future trends. View Now

Emerging Trends in Metadata Management

This report evaluates each question posed in a recent survey and provides subsequent analysis in a detailed format that includes the most noteworthy statistics, direct comments from survey respondents, and the influence on the industry as a whole. It seeks to present readers with a thorough review of the state of Metadata Management as it exists today. View Now

Business Intelligence versus Data Science


The competitive advantages realized from a dependable Business Intelligence and Analytics (BI/A) program are well documented. Everything from reduced business costs and increased customer retention to better decision making and the ability to forecast opportunities have been observed outcomes in response to such programs. View Now

Insights into Modeling NoSQL

The growth of NoSQL data storage solutions have revolutionized the way enterprises are dealing with their data. The older, relational platforms are still being utilized by most organizations, while the implementation of varying NoSQL platforms including Key-Value, Wide Column, Document, Graph, and Hybrid data stores are increasing at faster rates than ever seen before. Such implementations are causing enterprises to revise their Data Management procedures across-the-board from governance to analytics, metadata management to software development, data modeling to regulation and compliance. View Now

Navigating the Data Governance Landscape: Analysis of How to Start a Data Governance Program

This report analyzes many challenges faced when beginning a new Data Governance program, and outlines many crucial elements in successfully executing such a program. View Now

Cognitive Computing: An Emerging Hub in IT Ecosystems

Will the “programmable era” of computers be replaced by Cognitive Computing systems which can learn from interactions and reason through dynamic experience just like humans? View Now

Status of the Chief Data Officer: An Update on the CDO Role in Organizations Today

Ask any CEO if they want to better leverage their data assets to drive growth, revenues, and productivity, their answer will most likely be “yes, of course.” Ask many of them what that means or how they will do it and their answers will be as disparate as most enterprise’s data strategies. To successfully control, utilize, analyze, and store the vast amounts of data flowing through organization’s today, an enterprise-wide approach is necessary. View Now

Why Your Business Users Need to Love Metadata

No business likes to throw money out the window, or in the case of the modern day enterprise, down the electronic data stream. View Now

The Question of Database Transaction Processing: An ACID, BASE, NoSQL Primer

There are actually many elements of such a vision that are working together. ACID and NoSQL are not the antagonists they were once thought to be; NoSQL works well under a BASE model, but also some of the innovative NoSQL systems fully conform to ACID requirements. View Now

The Utilization of Information Architecture at the Enterprise Level

This report investigates the level of Information Architecture (IA) implementation and usage at the enterprise level. The primary support for the report is an analysis of a 2013 DATAVERSITY survey on Data and Information Architecture. View Now

Unstructured Data and the Enterprise

In its most basic definition, unstructured data simply means any form of data that does not easily fit into a relational model or a set of database tables. Unstructured data exists in a variety of formats: books, audio, video, or even a collection of documents. In fact, some of this data may very well contain a measure of structure, such as chapters within a novel or the markup on a HTML Web page, but not a full data model typical of relational databases. View Now

Three-Valued Logic

Much has been written and debated about the use of SQL NULLs to represent unknown values, and the possible use of three-valued logic. View Now

An Approach to Representing Non-Applicable Data in Relational Databases

Ever since Codd introduced so-called “null values” to the relational model, there have been debates about exactly what they mean and their proper handling in relational databases. View Now

NO E-R: Modeling for NoSQL Databases

Entity-relationship (E-R) modeling is a tried and true notation for use in designing Structured Query Language (SQL) databases, but the new data structures that Not-Only SQL (NOSQL) DBMSs make possible can’t be represented in E-R notation. View Now

Cardinality, Optionality, and Unknown-ness

This paper explores the differences between three situations that appear on the surface to be very similar: a data attribute that may occur zero or one times, a data attribute that is optional, and a data attribute whose value may be unknown. View Now

A Systematic Solution to Handling Unknown Data in Databases

Ever since Codd introduced so-called “null values” to the relational model, there have been debates about exactly what they mean and their proper handling in relational databases. View Now

The Hybrid Data Model

NoSQL database management systems give us the opportunity to store our data according to more than one data storage model, but our entity-relationship data modeling notations are stuck in SQL land. View Now

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