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Self-Optimizing Cloud Data Virtualization Guidebook Image

SOLUTION BRIEF:

Self-Optimizing Cloud Data Virtualization

Learn how data virtualization serves as a smart acceleration layer on data lakes, which remains the single source of truth, and runs in the customer cloud environment (VPC). Solution platforms can enable data teams to operationalize the entire data lake while ensuring interactive performance, without the need to move data, model or manually optimize.
 
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Athena

ATHENA WHITE PAPER:  

How to Close the Data Virtualization Gap

Data virtualization has become synonymous with reducing data duplication and lowering the cost of both data-ops and devops. It allows administrators to maintain access control 
 and provide audits of data access. 
 
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ARTICLE:

3 Common Pitfalls to Embracing the Data Lake Architecture with AWS Athena


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The New Standard for Data Visualization - iPad Cover

GUIDEBOOK:

The New Standard for Data Virtualization

This guidebook will go over the new standards that data virtualization must meet to game change your data and analytics efficiencies as well as cost savings.

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Gartner

Varada Named a ‘Cool Vendor in Data Management’ 

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ARTICLE:

5 Tips to better Manage Your Presto Clusters

The benefits delivered by Presto are tremendous, but is it really running as efficiently as possible? Can it support the SLA on response time and concurrency that workloads and users demand?  

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TWO-PAGER:

5 Obstacles To Connecting BI Tools To Your Data Lake

The more data exists on a cloud data lake, the harder it becomes to deliver interactive BI. When trying to run queries on backend tools such as AWS Athena or Presto, you may run into these fundamental challenges that will ultimately drive you to look for other optimized solutions.
 
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ARTICLE:

Why Visibility is Critical for Success in Enterprise Data Analytics

As a data team, you’re drowning in demand from users requesting analytics access to your corporate data lake. There’s a good reason to welcome these requests. You can handle these user requests in one of two ways: either start to move subsets of data out to externally managed systems or provide a query engine to access data directly in the data lake.

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ARTICLE:

How to Avoid Trading DevOps Savings for DataOps Costs

Outsourced DataOps services are great to get started but they come with hidden costs. The hardest to identify and easiest to address is the increase in DataOps workloads. More users means more queries but not necessarily proportionally higher budgets.

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Presto Workload Analyzer

Get the free Presto Workload Analyzer to uncover deep actionable insights, improve performance and optimize your Presto clusters.
  • Are you challenged with performance concerns in your Presto environment?
  • How are you optimizing your Presto cluster?
  • Can you identify who or what is sapping resources?
View a Sample Report
Download the Workload Analyzer

There's a New Standard for Data Virtualization

Meet Varada. 

With the use of dynamic analysis and adaptive indexing data architects are able to seamlessly accelerate and optimize workloads - resulting in optimal control over performance and cost. 

Curious to learn more? Pick a time, and let's Zoom!