Click to learn more about author Kartik Patel. If Data Science was once the sole domain of analysts and data scientists, Augmented Data Science represents the democratized view of this domain. With Augmented Data Science, the average business user can engage with advanced analytics tools that allow for Automated Machine Learning (AutoML) and leverage sophisticated analytical […]
Leveraging Natural Language Processing Within a CDP
Click to learn more about author Jonathan Lee. In my last column for DATAVERSITY I sought to define the concept of a Customer Data Platform (CDP), noting that a CDP “creates a comprehensive view of each customer by capturing data from multiple systems.” What I didn’t do however, was to delve into a discussion of […]
Nowcasting Chicago Crime with R
Click to learn more about author Steve Miller. In my many years as a data scientist, I’ve spent more time doing forecast work than any other type of predictive modeling. Often as not, the work’s involved forecasting demand for an organization’s many products/lines of business a year or more out based on five or more […]
Three Lessons Data Management Can Learn from Meal Delivery Services
Click to learn more about author Lisa Spagnolie. Enterprises today are acutely aware of the exponential growth of data. However, according to a survey by PricewaterhouseCoopers, only 15% of firms currently have access to the right data needed to achieve their goals. In the face of massive data overload, today’s enterprises don’t have time to […]
Lucidworks Announces Fusion 4.2 With New Predictive Merchandising Feature
A new press release reports, “Lucidworks, leader in AI-powered search applications, today announces the release of Lucidworks Fusion 4.2, the latest version of their development platform that incorporates machine learning and AI technologies into search applications. The release includes increased usability for product owners and domain experts to easily deploy AI-powered solutions to build a […]
Data Architect vs. Data Engineer
The data architect and data engineer work in tandem – conceptualizing, visualizing, and then building an Enterprise Data Management Framework. The data architect visualizes the complete framework and creates the blueprint, which the data engineer uses to build the “digital framework.” The data engineering role has recently evolved from the traditional software-engineering field. Recent Enterprise […]
Is it Time to Drain the Data Lake?
Click to learn more about author Karthik Ramasamy. It sounds appealing – easily store all of your data in a single location, where all of your users and applications can access it and put it to use. It’s no wonder that interest in data lakes rose rapidly at the same time hype around “Big Data” was […]
The State of Data Education: Bringing IT and the Business Together
There’s something missing in the way that many higher education institutions educate students about the intersection between technology and business. The problem: they often don’t. There just isn’t enough focus on getting those people who are studying the science – and art – of working with data to also work in tandem with business peers […]
What is Automated Machine Learning (AutoML)?
Click to learn more about author Kartik Patel. What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals. With the right tools, today’s average business user […]
Big Data Integration 101: The What, Why, and How
Big Data Integration is an important and essential step in any Big Data project. There are, however, several issues to take into consideration. Generally speaking, Big Data Integration combines data originating from a variety of different sources and software formats, and then provides users with a translated and unified view of the accumulated data. Managing […]