Data Science Data Warehouse Optimization Structured Data 
Smart Data Collective
SEPTEMBER 23, 2020
The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.
CIO Business Intelligence
APRIL 25, 2022
“You can think that the general-purpose version of the Databricks Lakehouse as giving the organization 80% of what it needs to get to the productive use of its data to drive business insights and data science specific to the business. Features focus on media and entertainment firms.
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CIO Business Intelligence
NOVEMBER 14, 2022
A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.
CDW Research Hub
APRIL 20, 2020
Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications. Connecting ThoughtSpot and Snowflake is a simple 3-step process.
AWS Big Data
MARCH 7, 2023
Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Data lakes are more focused around storing and maintaining all the data in an organization in one place.
Cloudera
MAY 17, 2021
Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.
AWS Big Data
JUNE 6, 2023
In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.
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