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Upcoming Webinars

Jun 3 DGPO Webinar: Electrifying the Data Culture at Hydro One

DATE: June 3, 2020 TIME: 2 PM Eastern / 11 AM Pacific PRICE: Free to all attendees This Webinar is Developed by: About the Webinar This is a story of how a small data team changed the data culture of a large electrical utility with $27.1B(1) in assets. Focusing on the…

Jun 9 DataEd Webinar: Approaching Data Governance Strategically

DATE: June 9, 2020 TIME: 2 PM Eastern / 11 AM Pacific PRICE: Free to all attendees About the Webinar At its core, Data Governance (DG) is: managing data with guidance. This immediately provokes the question: Would you tolerate your data managed without guidance? (In all likelihood, your organization has…

Latest Blogs by Industry Experts

Building the Data-Driven Enterprise for a Resilient Future

Click to learn more about author Bas Kamphuis Confronted with the current state of the world, business leaders are reassessing and recalibrating how they can better prepare themselves to become more resilient across their supply chain, their financial and customer operations, and the protection of their employees. Early in 2020, many companies were already looking to innovate faster; now, the imperative for data-driven insights and digital execution is a first-order…

The Virtual Chief AI Officer: A Critical Advisor to the C-Suite

Click to learn more about author Asha Saxena. AI's rapid surge in value-add has left companies struggling to adopt this highly complex technology. Executives struggle to understand it. At a basic level, the terminology is confusing — machine learning, deep learning, computer vision, computational statistics, cognitive computing, natural language/speech processing, robotic process automation (RPA), AI, etc. The business use cases are unclear, and the experts are mostly in academia, have their…

Maintaining Data Integrity During Integration

Click to learn more about author Ibrahim Surani Every organization integrates and shares data with multiple systems, processes, and individuals. With data being generated and consumed at unprecedented levels, the challenge is ensuring its integrity before it’s processed or fed into reporting and analytics databases. Consider a scenario, where you have to decide whether to invest next quarter’s marketing budget in campaign A or B. Imagine making that decision based…

Case Studies

What is...?

What is Data Storage?

Data storage describes what type of, where, and how hardware or software holds, deletes,…

What is BASE?

BASE describes database processing germane to a NoSQL database, such as a data lake.…

What is ACID?

ACID properties characterize RDBMS (Relational Database Management System) database processing or a data warehouse.…

Most Recent Articles

The Future of Data Engineering

A Data Engineering Guide reveals that while people often rely on the work of data engineers — depending on Siri for quick solutions or being enchanted by custom recommendations or promos — they often do not realize that these advanced tools can provide accurate results only because of the hard work put in by data engineers. The analysis conducted on big data showed it is only as good as Data…

Data-Centric Architecture: Find Value with a Data Platform Approach

Applications provide a way to capture raw data in forms and store it in databases, and automated processes make it possible to extract meaning from that data using application programming interfaces (APIs). The current process-centric mindset assumes that the value resides in the automated processing, yet the limitations and costs inherent in its reliance on APIs have led to a re-examination of priorities and new thinking about where data value…

Graph Databases vs. Key-Value Databases

Graph databases and key-value databases have very different features and are used for accomplishing different tasks. Key-value databases are streamlined and fast, but are limited and not as flexible. Graph databases, on the other hand, are very flexible and great for research, but not terribly fast. Both typically use a non-relational foundation. The two key strengths of graph databases are their flexibility and their focus on relationships. Graph databases are…

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. Multiple options exist for starting small and scaling up an analytics program, according to Evan…

Case Study: Tracking and Tracing Drugs in the Pharmaceutical Supply Chain

Failures or lack of visibility in the many-tiered pharmaceutical supply chain have multiple repercussions. Drug shortages have adverse economic and clinical effects on patients — they are more likely to have increased out-of-pocket costs, rates of drug errors, and, yes, mortality. Hospitals and health systems allocate over 8.6 million hours of additional labor hours to manage drug shortages each year at a cost of at least $360 million, with alternative…

Business Intelligence Meets Metadata Challenges

Many BI managers, CEOs, and CIOs cannot afford to add more staff, so they are seeking technologies that can help their existing teams operate more accurately and efficiently. They “need to change the physics, as we call it. They can’t just add more people to the team,” said Amnon Drori in a recent DATAVERSITY® interview. To have manual work done on premise using professional services combined with a variety of…

Latest Industry News

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