Dave is the founder of AtScale and is the Chief Technology Officer. Prior to AtScale, he was VP of Engineering at Klout & at Yahoo! where he built the world’s largest multi-dimensional cube for BI on Hadoop. Mariani is a Big Data visionary & serial entrepreneur.
March 22, 2024
Power BI Face Off: Databricks vs. Microsoft FabricAs I hinted in my last blog post, “Your Questions Answered: TPC-DS Benchmark for Power BI/Direct Lake”, and due to popular customer demand, I’m happy to announce that we just published our Power BI/Direct Lake benchmark comparison for another data…
February 22, 2024
Your Questions Answered: TPC-DS Benchmark for Power BI/Direct LakeI’ve received quite a bit of feedback since releasing our TPC Benchmark on Power BI/Direct Lake report a few weeks ago. In online forums and in conversations with customers, prospects and partners, I collected the feedback and decided to use…
September 26, 2023
Modernize Legacy BI and OLAP Workloads with AtScale and Google BigQueryThis post is authored in partnership with Naveen Punjabi, Director of Analytics and Data Science Partnerships at Google Cloud. An original version of the post was initially published on the Google Cloud Blog. A partnership that brings new economics and…
July 13, 2023
The 6 Principles of Modern Data ArchitectureOne of my favorite parts of my job at AtScale is spending time with customers and prospects. More specifically, I enjoy learning what matters most to them as they move to modern data architecture. I've noticed six main themes that…
June 29, 2023
Preventing Semantic Sprawl in the Modern Data Analytics StackData is invaluable to an organization’s decision-making, business innovation, and cross-team collaboration. With the rise of big data and cloud data warehouses, fully-realized democratization is the next step in many businesses’ data journeys. They want to enable company-wide, self-service analytics,…
June 15, 2023
A Federated Data Model Governance Approach: Insights from Data LeadersI hosted another round of interviews with data leaders about how they deliver AI and BI for their organizations. We discussed the combining of data fabric and data mesh, the hub-and-spoke approach, and the future of a federated model for…
June 1, 2023
Choosing the Right Semantic Layer Strategy for Your Organization’s Data StackThe average data platform holds raw data assets from several different locations — BI apps, data warehouses, reports, etc. This becomes a challenge when teams need an effective way to unite and leverage this entire ecosystem for intelligent decisions and…
April 26, 2023
High Code v. Low Code v. No Code Data ModelingWhen my co-founders and I launched AtScale almost ten years ago, we set out to democratize analytics consumption for everyone, not just database experts. We were dismayed to see the new generation of visualization tools forcing their users to become…
January 10, 2023
Data Analytics is The Foundation of an Enterprise AI StrategyThere 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…
December 20, 2022
Using Augmented Analytics for Predictive and Prescriptive AnalysesThere 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…
December 15, 2022
How to Maximize the Value of AI and BI at ScaleA 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,…
December 6, 2022
Deploying “Data as Code” Throughout the Entire EnterpriseHow 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…