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Fighting for the Poetry in the Data Space

Click to learn more about video blogger Scott Taylor. The Data Rants video blog series begins with host Scott Taylor "The Data Whisperer."  The series covers some of the most prominent questions in Data Management such as Master Data, the difference between Master Data and MDM, "truth" versus "meaning" in data, Data Quality, and so much more. In today’s video blog Scott discusses the complicated task of working to better…

Regularization for Logistic Regression: L1, L2, Gauss or Laplace?

Click to learn more about author Kathrin Melcher. Regularization can be used to avoid overfitting. But what actually is regularization, what are the common techniques, and how do they differ? Well, according to Ian Goodfellow [1]: “Regularization is any modification we make to a learning algorithm that is intended to reduce its generalization error but not its training error.” In other words: regularization can be used to train models that…

Updating Your Network Data Infrastructure in 2020

Click to learn more about author Jason Carolan. As the promise of 5G creeps slowly into the present day, the ways certain technologies and industries will be affected or transformed once the technology is in place are coming into focus. While many businesses cannot say they are using 5G today, many are experiencing its initial impact as the fiber roll-out to prepare for 5G takes place. Over the next year…

Case Studies

What is...?

What is a Data Analyst?

Data analysts help businesses make better, more informed decisions by not only collecting and…

What is a Data Architect?

A data architect provides clear specifications, models, and definitions, translating a business’ Data Strategy…

What is a Data Engineer?

Data engineers build Data Architecture  through infrastructures and foundations. A data engineer is tasked…

What is Data Literacy?

Data literacy describes the ability to read, work with, analyze, and argue with data,…

What is DataOps?

DataOps (Data Operations) is collaborative Data Management practices “focused on improving the communication, integration,…

What is a Data Scientist?

Data scientists emphasize rigor and performance when obtaining, scrubbing, exploring, modeling, and interpreting data.…

Most Recent Articles

Case Study: JTC Grows its Cloud Services Core though Trust and Teamwork

Trust, teamwork, and technology form the core of Jewell Technical Consulting, Inc. (JTC) and its partnership with Leaseweb USA, a leading hosting and cloud services company whose offerings include Infrastructure-as-a-Service (IaaS) solutions. JTC, a company providing private cloud services to North Virginia and D.C. metro businesses, was originally utilizing another hosting facility 20 miles way from its Manassas, Virginia headquarters. But as JTC grew, the two- to three-hour round trips…

Data Architects, It’s Time to Improve Your Data Classification

Team Data — data architects in particular, whatever their official title may be — have a job to do. That is to take more aggressive steps to protect data assets on behalf of customers and constituents. The responsibility falls to data architects because few in most organizations are thinking about protecting data from the data point of view, so to speak. The lawyers and the security group think about it…

Business Intelligence and Analytics Trends in 2020

The general pattern of technology upgrades in Enterprise Analytics & Business Intelligence that occurred in 2019 signaled the emergence of some specific types of analytics: smart, real-time, augmented, and conversational. These trends will continue growing well into 2020 and beyond. Also included in that list are: Smart devices and multi-channel data will require smart analytics tools for improved insights; real-time analytics will be a necessity in the era of sensors…

Understanding the Uses of Artificial Intelligence

Artificial intelligence (AI) has provided a critical competitive advantage for those organizations able and willing to use it. AI has gained significant momentum in the last few years, acting as personal assistants for some, while processing business transactions and providing technical services to others. AI systems have the ability to manage large amounts of data in a number of ways. Different types of artificial intelligence have been evolved to handle…

Case Study: Deriving Spark Encoders and Schemas Using Implicits

Click to learn more about author Dávid Szakallas. In recent years, the size and complexity of our Identity Graph, a data lake containing identity information about people and businesses around the world, begged the addition of Big Data technologies in the ingestion process. We used Apache Pig initially, and then migrated to Apache Spark a couple of years ago. Here is a closer look at our journey and vital lessons…

Data Strategy vs. Business Strategy

For any transformational Business Strategy, data-driven intelligence must be “readily accessible, interpretable, and actionable” whenever necessary. At the macro level, a data-driven culture has to be consciously propagated throughout the organization, end-to-end. Digital businesses have acknowledged the importance of data accessibility and have embraced this culture within their business model to remain competitive. The late adopters or data-culture beginners can more quickly adapt to a data-driven Business Strategy by aligning…

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