Evolution of Data Management From Presumption driven to Data driven Background
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Accelerate Time To Business Value from Azure SQL Data Warehouse or HDInsight With Paxata Self-Service Data Preparation

July 16, 2018
· 3 min read

Whether you view data as fuel for your digital transformation or whether you call it the oil in the modern economy, the reality is that it’s probably all of that and much more. Actionable insights are locked up in your data – insights that can help deliver better customer experiences, create new products and help optimize your business processes end to end. But for all the hype around becoming data driven, strong positive outcomes are elusive for many.

A Changing Data Landscape

One of the key reasons why organizations struggle is that data has gone from being captured and stored in a few applications, probably in your own data center, to being created and stored everywhere. Our old on-premises apps are replaced by best of breed apps in the cloud, sensors on products are streaming data from the edge. Every web site today captures every click or page view. The bottom line is that there are lots of data – both in terms of volumes as well as types and locations – and all of this data needs to be managed, accessed, cleaned in order to deliver the desired actionable insights.

A Change in Lifestyle

Perhaps one of the most underappreciated aspects is that our lifestyle for data management and analytics must change. Gone are the days when we would predefine a few analytical scenarios and build an enterprise data warehouse (EDW) and the associated extract, transform, load (ETL) data preparation process.

Today we store all the data we can get our hands on – with little to no concern for its structure or shape. Shape and structure is a function of the analytical process and is not predefined, giving rise to the new paradigm for extract, load, transform (ELT) when we think of data preparation.

The New Normal: Enterprise Self-Service Data Preparation at Scale

The new normal for leading data driven organizations is to empower those business users with the context of what the data means and have a deep understanding of the business to prepare their own datasets for use in analytical processes. As outlined above, too many organizations try to solve today’s data challenges with tools designed for a different time and skillset. A modern self-service data prep solution can accelerate time to insights and associated business outcomes.

Paxata Self-Service Data Preparation for Azure SQL Warehouse

Paxata is a leading provider of enterprise grade self-service data preparation solutions and is the only Microsoft Preferred Solution in the data prep space.

There are two main areas where Paxata can help accelerate value for Azure SQL Warehouse deployments:

  • Data onboarding into Azure SQL Data Warehouse or HDInsight.
    Azure SQL Warehouse provides an agile data platform in the cloud that can elastically scale out as you need. Of course, getting data into the SQL Warehouse can become a bottleneck if we rely on our old style tools. Paxata’s Self-Service Data Preparation solution can get developers, business users and data analysts all in the same zero coding paradigm to collect and move data rapidly into the SQL Warehouse.
  • Data preparation from Azure SQL Warehouse for analytical uses with PowerBI
    Quite often an analytical initiative will still require bringing data together from data sources that might not all be pre-loaded into the SQL Warehouse. It could be personal CSV files or partner data. Paxata can help the business user to discover, clean, enrich and shape these disparate data sets into an analytical dataset.
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About the author

Value-Driven AI

DataRobot is the leader in Value-Driven AI – a unique and collaborative approach to AI that combines our open AI platform, deep AI expertise and broad use-case implementation to improve how customers run, grow and optimize their business. The DataRobot AI Platform is the only complete AI lifecycle platform that interoperates with your existing investments in data, applications and business processes, and can be deployed on-prem or in any cloud environment. DataRobot and our partners have a decade of world-class AI expertise collaborating with AI teams (data scientists, business and IT), removing common blockers and developing best practices to successfully navigate projects that result in faster time to value, increased revenue and reduced costs. DataRobot customers include 40% of the Fortune 50, 8 of top 10 US banks, 7 of the top 10 pharmaceutical companies, 7 of the top 10 telcos, 5 of top 10 global manufacturers.

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