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MongoDB Enhances Developer Data Platform

David Menninger's Analyst Perspectives

While new and emerging capabilities might catch the eye, features that address data platform security, performance and availability remain some of the most significant deal-breakers when enterprises are considering potential data platform providers. This is especially true for mission-critical workloads. Regards, Matt Aslett

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The Increasing Importance of Open Table Formats

David Menninger's Analyst Perspectives

I previously wrote about the importance of open table formats to the evolution of data lakes into data lakehouses. The concept of the data lake was initially proposed as a single environment where data could be combined from multiple sources to be stored and processed to enable analysis by multiple users for multiple purposes.

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Einstein Studio 1: What it is and what to expect

CIO Business Intelligence

The company has been bundling various forms of automation into its Einstein brand since 2016. With this platform, Salesforce seeks to help organizations apply the cleverness of LLMs to the customer data they have squirreled away in Salesforce data lakes in the hopes of selling more. This isn’t a new push for Salesforce.

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Capital One Offers Cost Controls for Cloud Data Warehouses

David Menninger's Analyst Perspectives

The adoption of cloud environments for analytic workloads has been a key feature of the data platforms sector in recent years. For two-thirds (66%) of participants in ISG’s Data Lake Dynamic Insights Research, the primary data platform used for analytics is cloud based.

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Build and manage your modern data stack using dbt and AWS Glue through dbt-glue, the new “trusted” dbt adapter

AWS Big Data

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities.

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A Few 2016 Technology Predictions

In(tegrate) the Clouds

I enjoy the end of the year technology predictions, even though it’s hard to argue with this tweet from Merv Adrian: By 2016, 99% of readers will be utterly sick of predictions. 2016 will be the year of the data lake. 2016 will be the year of the data lake. I can’t help it.

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Thermo Fisher transforms its customer experience

CIO Business Intelligence

in 2016, and BD Advanced Bioprocessing in 2018. The rapid growth left the company highly dependent on fragmented, manual processes and disparate data sources and systems. The team also built a centralized data lake on AWS, Databricks, and Power BI. in 2013, Alfa Aesar in 2015, Affymetrix and FEI Co. Catalyzing change.

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