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Putting the Business Back Into Business Innovation

Timo Elliott

The industry analysts all have a similar vision of what that agile future of business looks like. Most innovation platforms make you rip the data out of your existing applications and move it to some another environment—a data warehouse, or data lake, or data lake house or data cloud—before you can do any innovation.

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Top Data and Analytics Posts of 2019

Sisense

5 Advantages of Using a Redshift Data Warehouse. Whatever business you’re in, your company is becoming a data company. That means you need to put all that data somewhere. Chances are it’s in a data warehouse, and even better money says it’s an AWS data warehouse. A vision for the future.

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Deriving Value from Data Lakes with AI

Sisense

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. The right data and analytics platform can help you bridge the gap between your current AI and analytics paradigm and where you want your company to be in the future. .

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Meet Delta Sharing: Access more data with secure, open source data sharing

Tableau

Take advantage of the open source and open data formats of Delta Lake to make data accessible to everyone . Work with any data warehouse or data platform that supports Parquet. Databricks shares our belief in fostering a data culture to fuel innovation. Provide strong security, governance, and auditing.

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Tableau Partners recognized in annual awards for driving customer success

Tableau

Tableau executives discussed our vision, strategy, and specific areas of focus globally and by Theater that we can together best support our mutual customers and community. Snowflake enables customers to store and analyze data efficiently—giving them the ability to scale their data warehouse up and down with demands.

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The Ultimate Guide to Data Warehouse Automation and Tools

Insight Software

This puts tremendous stress on the teams managing data warehouses, and they struggle to keep up with the demand for increasingly advanced analytic requests. To gather and clean data from all internal systems and gain the business insights needed to make smarter decisions, businesses need to invest in data warehouse automation.

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It’s Time for Data Historians to Become … History

Actian

There are many Operational Technology (OT) environments within manufacturing, oil and gas, engineering research, and countless other industries where complex equipment, machinery, and networks of sensors and devices generate time-series data. Modern Time-Series Databases capture multi-modal data.