David Menninger's Analyst Perspectives
NOVEMBER 7, 2024
Capital One began its transition to a cloud-first company in 2016 and completed its migration away from on-premises data centers to the cloud in 2020. Along the way, it adopted Snowflake’s AI Data Cloud and became an investor in the company in 2017.
Alation
FEBRUARY 20, 2020
Considering what we’ve seen this year in industry trends and patterns, we have compiled some predictions for 2016 from our co-founders at Alation. Venky Ganti, CTO & Co-Founder: Data sprawl will finally hit its threshold. Data sprawl has been prevalent for several years. 2016 will be the year of the “logical data warehouse.”
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In(tegrate) the Clouds
DECEMBER 21, 2015
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. In 2016, which software company will be the biggest game-changer for the long term?
Sisense
APRIL 24, 2019
In organizations that operate without a data warehouse or separate analytical database for reporting, the only source of the latest and up-to-date data may be in the live production database. For example, let’s assume 200 sales have been made in the year 2016, and we want to query for the number of sales per customer in 2016.
AWS Big Data
NOVEMBER 29, 2023
dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.
David Menninger's Analyst Perspectives
OCTOBER 31, 2024
It was not until the addition of open table formats— specifically Apache Hudi, Apache Iceberg and Delta Lake—that data lakes truly became capable of supporting multiple business intelligence (BI) projects as well as data science and even operational applications and, in doing so, began to evolve into data lakehouses.
BizAcuity
FEBRUARY 1, 2019
billion US dollars in 2016, up from 29.3 The solution here is to consolidate all of this data, gathered from different points at different times along the course of the event and store it in one consolidated form in a Data Warehouse. One of the many things that data warehouses allow is the chronological sifting of data.
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