4 Key Data Prep Capabilities to Create a Single View of Customer Vendor Background

Self-Service Data Prep to Accelerate MicroStrategy Analytics

May 21, 2018
· 3 min read

Data in a multi-cloud hybrid world

Traditional data analytics environments were built on the Enterprise Data Warehouse (EDW) usually running in some relational database like Teradata, Microsoft, or Oracle. While those still exist, there are many more sources that analysts need to get access to in order to perform the kinds of analytics required.

  • Big data/Hadoop: increasingly, the modern EDW is not limited to an RDBMS but is augmented by Hortonworks or Cloudera, containing data that did not fit into the EDW. Think of smart meter data for a utility company. Data Lakes which were once ‘science projects’ and ‘prototypes’ are fast becoming mainstream options for organizations. A Data Lake strategy is often a key initiative for a CDO and CIO to not only make the data more accessible to business SME’s, but also provide a lower cost alternative for the organization.
  • Multi-cloud: Many organizations are opting to run their data workloads in the cloud, either using native cloud services like Azure HDInsight or AWS EMR. In addition, many organizations are running their Cloudera or Hortonworks workloads in Virtual Private Cloud (VPC) environments as well.
  • Ephemeral or Transient workloads: One other dynamic that is shaping the data landscape is the growing requirement of analytical teams needing to pull data together from a variety of sources and create an ephemeral sandbox for their project.

Moving Towards Agile Analytics

In addition to the explosion of data sources and locations, the way we do analytics has changed. Rather than predefining how questions will be answered with the data, we now live in a world where often we want all the data and rather let the data tell us what questions it could answer. And to achieve insights in an iterative, exploratory manner.

Self-Service Data Preparation Becomes the Enabler

The only way to empower the business actionable insights is to provide them with self-service data preparation. Data prep is the process of finding, ingesting, profiling, cleansing, enriching, shaping, and provisioning data from a diverse set of raw data sources. Empowering your business users and analysts to do this by themselves with full enterprise governance and collaboration with peers brings a new scale to decision making and innovation for your business. In addition, it frees valuable, scarce IT resources to focus on other mission critical endeavors.

Data Prep and MicroStrategy

Data Prep’s Adaptive Information Platform is the leading business user self-service data preparation solution in the market. What makes our solution unique is:

  • Designed to cater for non-technical business users
  • Visual, interactive data discovering, shaping, enriching with intelligent recommendations and guides to help you clean and shape your data
  • Zero coding required
  • Algorithmic intelligence and smart suggestions
  • No sampling, uses Spark for enterprise data volumes
  • Enterprise class governance and security
  • Available on premises and the cloud

In the latest version of our platform we now offer out of the box one-click publishing of AnswerSets to be published as MicroStrategy Intelligent Cubes. Some of the unique benefits this brings to the MicroStrategy analysts:

  • Ability of a BI developer/analyst to own the end-to-end cycle of accessing raw data, prepping the data, publishing the data and building their BI and/or mobile applications in MicroStrategy
  • Easy access to modern data sources like Azure HDI, Hadoop, EMR, JSON files etc.
  • Visual, interactive self-service data prep on the fly in a zero coding interface
  • One-click publishing of AnswerSets that automates the publishing of data into MicroStrategy Dashboards or reports
  • Easy automation and scheduling of data prep routines

Join us at MicroStrategy Symposium Chicago

If you are planning on attending the MicroStrategy Symposium in Chicago on May 21, please come listen to our session (Self-Service Data Prep at Scale from 2:45 – 3:30 pm PT) or visit our booth for a demo. 

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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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