Some striking evidence of the impact of bad data can be found in fake email IDs, impersonations on social media, or misuse of stolen financial or personal information. The more widespread harm can be caused by bad data in Data Analytics, where anything from the wrong medical diagnosis to incorrect interpretation of stock history can […]
What Is Data Science?
Data Science is a combination of scientific disciplines “to build predictive models that explore data content patterns,” according to the Data Management Body of Knowledge (DMBoK). Data Science, formerly known as applied statistics: “Integrates methods from mathematical, statistical, computer science, signal processing, probability modelling, pattern recognition machine learning, uncertainty modeling and data visualization towards gaining […]
Webinar: How to Accelerate BI Responsiveness with Data Lineage
This webinar was sponsored by: About the Webinar In an ever-growing data landscape, BI teams find it hard to navigate and comprehend complex movements of data between several systems as well as within each system. Data lineage is often described as horizontal or vertical movement of data, but if the universe of data could be […]
Slides: How to Accelerate BI Responsiveness with Data Lineage
How to Accelerate BI Responsiveness with Data Lineage from DATAVERSITY This webinar was sponsored by: About the Webinar In an ever-growing data landscape, BI teams find it hard to navigate and comprehend complex movements of data between several systems as well as within each system. Data lineage is often described as horizontal or vertical movement […]
What Is Data Ethics?
Data Ethics describe a code of behavior, specifically what is right and wrong, encompassing the following: Data Handling: generation, recording, curation, processing, dissemination, sharing, and use. Algorithms: AI, artificial agents, machine learning, and robots. Corresponding Practices: responsible innovation, programming, hacking, and professional codes. Data Ethics build on the foundation provided by computer and information ethics, but […]
White Paper: The Case for Embedding Analytics in Your Product
Timing is Everything — The Case for Embedding Analytics in Your Product Sooner Rather Than Later About the White Paper Regardless of your industry, the customers of today want and expect that their products deliver one critical element on top of your product’s base functionality. They want their data. They want to see with their […]
The Digital Mesh: How is it Changing Enterprises?
Is this a science fiction movie? No, the digital mesh — the long-awaited gift of connected technologies — is here now. Advanced science and telecommunications technologies together triggered the latest technology disruption, enabling people, processes, and digital devices to engage in a way that is vital for the survival of modern businesses. Landmark Digital Disruption: […]
ADV Webinar: Platforming the Major Analytic Use Cases for Modern Engineering
To view just the slides from this presentation, click HERE>> About the Webinar We’ll describe some use cases as examples of a broad range of modern use cases that need a platform. We will describe some popular valid technology stacks that enterprises use in accomplishing these modern use cases of customer churn, predictive analytics, fraud […]
ADV Slides: Platforming the Major Analytic Use Cases for Modern Engineering
Platforming the Major Analytic Use Cases for Modern Engineering from DATAVERSITY To view just the On Demand recording of this presentation, click HERE>> About the Webinar We’ll describe some use cases as examples of a broad range of modern use cases that need a platform. We will describe some popular valid technology stacks that enterprises […]
What Is Naïve Bayes Classification and How Is It Used for Enterprise Analysis?
Click to learn more about author Kartik Patel. What Is Naïve Bayes Classification? Naive Bayes is a classification algorithm that is suitable for binary and multiclass classification. It is a supervised classification technique used to classify future objects by assigning class labels to instances/records using conditional probability. In supervised classification, training data is already labeled with […]