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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

After launching industry-specific data lakehouses for the retail, financial services and healthcare sectors over the past three months, Databricks is releasing a solution targeting the media and the entertainment (M&E) sector. Features focus on media and entertainment firms.

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Peloton embraces Amazon Redshift to unlock the power of data during changing times

AWS Big Data

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

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What I Learned At Gartner Data & Analytics 2022

Timo Elliott

But Gartner is calling for something more sophisticated — for example, what they call Decision Intelligence , where you go beyond just providing information, and actually help reengineer and optimize decision processes. They say you need data artists that create great questions to complement the data scientists that find great answers.

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Extreme data center pressure? Burst to the cloud with CDP!

Cloudera

Burst to Cloud not only relieves pressure on your data center, but it also protects your VIP applications and users by giving them optimal performance without breaking your bank. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs. You are probably hesitant.

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Putting the Business Back Into Business Innovation

Timo Elliott

The future is enabled by technology, but it’s not about the technical infrastructures: it’s about optimizing end-to-end processes, business capabilities, and business ecosystems. You lose the roots: the metadata, the hierarchies, the security, the business context of the data. So how do organizations do that?

Data Lake 105
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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

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.

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Azure Data Sources for Data Science and Machine Learning

Jen Stirrup

You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics. It has native integration with other data sources, such as SQL Data Warehouse, Azure Cosmos, database storage, and even Azure Blob Storage as well. The data is also distributed. Azure Data Lake Store.