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Scaling the Analytics Team: Developing Key Roles

In an enterprise analytics team, different roles exist to fill different needs, and those needs must be met in order to be successful. Launching an analytics program doesn’t necessarily require a massive influx of personnel before producing usable insights from data, yet it’s important that critical roles are filled, whatever the size of the team. […]

Understanding DataOps

DataOps (data operations) has its roots in the Agile philosophy. It relies heavily on automation, and focuses on improving the speed and accuracy of computer processing, including analytics, data access, integration, and quality control. DataOps started as a system of best practices, but has gradually matured to a fully functional approach for handling data analytics. […]

Data Virtualization Use Cases

Data virtualization, in a nutshell, utilizes data integration without replication. In this process, a single “virtual” data layer is created to provide data services to multiple users and applications at the same time. Why Data Virtualization Is a Necessity for Enterprises explains how data virtualization helps tackle data movement challenges by making a virtual dataset […]

Hybrid Database Architectures Lead the Way

Hybrid databases have evolved in the last decade, with a focus on cloud environments. In 2013, Gartner created the term “Hybrid Transaction/Analytical Processing” (or HTAP), which is defined by Gartner as: “An emerging application architecture that ‘breaks the wall’ between transaction processing and analytics. It enables more informed and ‘in business real time’ decision making.” […]

Data-as-a-Service (DaaS): An Overview

As external data begins to gain importance in business analytics, data assumes a new role in global businesses. Now data is not only an organizational asset, but also a distinct revenue opportunity via data-related services offered under the umbrella term of “Data-as-a-Service” (DaaS). DaaS service providers are either replacing the traditional data analytics services or […]

Utilizing Business Intelligence with AI

Business intelligence (BI) is, in essence, new information that is not necessarily common knowledge and is sought to gain a competitive advantage over the competition. Business intelligence comes from a variety of sources, ranging from spies working for the competition to data mining. Contrary to the theme of several current articles, business intelligence is not […]

Advances in Natural Language Processing

Natural Language Processing (NLP) unlocks the ability of machines to read text, hear speech, and interpret words, and NLP has advanced greatly in the last five years. NLP improves data analytics, detects malware, and fights fake news. For example, using NLP the Citation-Informed Estimated Truth (CIET) software program identifies authentic news with a 78 percent […]

How Much Data Quality is Good Enough?

Ask the question “How much Data Quality is good enough?” and see some very puzzled and alarmed looks. Data Quality, comprising all activities making data fit for consumption, plays a fundamental role in trust, security, privacy, and competitiveness. Good Data Quality is critical because it fuels a surviving and thriving business. While it would be […]

Self-Service Analytics Use Cases

Self-service analytics offers dynamic reports to business users, who can analyze the data by sophisticated, in-built functions. This kind of user empowerment reduces reliance on IT staff. Moreover, self-service business intelligence (BI) capability may additionally equip users with external data access and built-in features to instantly generate finished reports. To use a complete range of […]