January 17, 2023

Using Self-Service Tools To Speed Up Data Product Development

This blog is part of a series from Vin Vashishta, Founder and Technical Advisor with V Squared. V Squared advises businesses on AI strategy, data product strategy, transformation, and data organizational build-out services. They have helped clients deliver products with…

Posted by: Vin Vashishta

January 12, 2023

The Definition of Data Mesh: What Is It and Why Do I Need One?

Today’s leading businesses prioritize data mesh. The modern data mesh craze ultimately came about to streamline data democratization – that is, making the right data available to the right people at the right time. Democratization is a huge departure from…

Posted by: Elif Tutuk

January 10, 2023

Data Analytics is The Foundation of an Enterprise AI Strategy

There is a massive global investment in enterprise AI. While the potential for AI-driven value is huge, organizations are struggling with a common set of challenges to realizing this potential: Lack of data scientists, difficulty in moving more models to…

Posted by: Dave Mariani

December 20, 2022

Using Augmented Analytics for Predictive and Prescriptive Analyses

There are six key areas for effectively consuming data for business insights: data, access, model, analyze, consume, and insights. For organizations looking to advance in each of these areas, AtScale’s Data and Analytics Maturity Model Workshop explains how teams can…

Posted by: Dave Mariani

December 15, 2022

How to Maximize the Value of AI and BI at Scale

A few weeks ago, I spoke with two industry experts to get a first-hand view of maximizing AI and BI at scale. The panelists included Deepak Jose, Global Head of On-Demand Data and Analytics Solutions at Mars, and Jigyasa Grover,…

Posted by: Dave Mariani

December 6, 2022

Deploying “Data as Code” Throughout the Entire Enterprise

How analysts consume data is a key factor in determining how quickly, accurately, and efficiently stakeholders can make data-driven decisions. Without the ability to freely and speedily share data insights, it can take a lot of time, effort, and expertise…

Posted by: Dave Mariani

December 1, 2022

Where The Semantic Layer Fits In Your Data Strategy

This blog is part of a series from Vin Vashishta, Founder and Technical Advisor with V Squared. V Squared advises businesses on AI strategy, data product strategy, transformation, and data organizational build-out services. They have helped clients deliver products with…

Posted by: Vin Vashishta

November 29, 2022

How Semantic Layer Helps Scale up DataOps

This blog is written by Vidhi Chugh, Staff Data Scientist at Walmart Global Tech. Vidhi is an award-winning AI/ML innovation leader who works at the intersection of data science, product and research teams to deliver business value and insights. She carries…

Posted by: Vidhi Chugh

November 17, 2022

Making Everyone a Power Data Analyst with a Semantic Layer

The number of data analysts at your organization is a limiting factor that determines how many stakeholders are able to make data-driven decisions. To make better-informed decisions, organizations need to increase the number of people with the tools and expertise…

Posted by: Dave Mariani

January 17, 2023

Using Self-Service Tools To Speed Up Data Product Development

This blog is part of a series from Vin Vashishta, Founder and Technical Advisor with V Squared. V Squared advises businesses on AI strategy, data product strategy, transformation, and data organizational build-out services. They have helped clients deliver products with…

Posted by: Vin Vashishta

January 12, 2023

The Definition of Data Mesh: What Is It and Why Do I Need One?

Today’s leading businesses prioritize data mesh. The modern data mesh craze ultimately came about to streamline data democratization – that is, making the right data available to the right people at the right time. Democratization is a huge departure from…

Posted by: Elif Tutuk

January 10, 2023

Data Analytics is The Foundation of an Enterprise AI Strategy

There is a massive global investment in enterprise AI. While the potential for AI-driven value is huge, organizations are struggling with a common set of challenges to realizing this potential: Lack of data scientists, difficulty in moving more models to…

Posted by: Dave Mariani

December 20, 2022

Using Augmented Analytics for Predictive and Prescriptive Analyses

There are six key areas for effectively consuming data for business insights: data, access, model, analyze, consume, and insights. For organizations looking to advance in each of these areas, AtScale’s Data and Analytics Maturity Model Workshop explains how teams can…

Posted by: Dave Mariani

December 15, 2022

How to Maximize the Value of AI and BI at Scale

A few weeks ago, I spoke with two industry experts to get a first-hand view of maximizing AI and BI at scale. The panelists included Deepak Jose, Global Head of On-Demand Data and Analytics Solutions at Mars, and Jigyasa Grover,…

Posted by: Dave Mariani

December 6, 2022

Deploying “Data as Code” Throughout the Entire Enterprise

How analysts consume data is a key factor in determining how quickly, accurately, and efficiently stakeholders can make data-driven decisions. Without the ability to freely and speedily share data insights, it can take a lot of time, effort, and expertise…

Posted by: Dave Mariani

December 1, 2022

Where The Semantic Layer Fits In Your Data Strategy

This blog is part of a series from Vin Vashishta, Founder and Technical Advisor with V Squared. V Squared advises businesses on AI strategy, data product strategy, transformation, and data organizational build-out services. They have helped clients deliver products with…

Posted by: Vin Vashishta

November 29, 2022

How Semantic Layer Helps Scale up DataOps

This blog is written by Vidhi Chugh, Staff Data Scientist at Walmart Global Tech. Vidhi is an award-winning AI/ML innovation leader who works at the intersection of data science, product and research teams to deliver business value and insights. She carries…

Posted by: Vidhi Chugh

November 17, 2022

Making Everyone a Power Data Analyst with a Semantic Layer

The number of data analysts at your organization is a limiting factor that determines how many stakeholders are able to make data-driven decisions. To make better-informed decisions, organizations need to increase the number of people with the tools and expertise…

Posted by: Dave Mariani