Table of Contents

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  1. About the Enterprise Data Preparation Administrator Guide
  2. Introduction to Enterprise Data Preparation Administration
  3. Getting Started
  4. Administration Process
  5. User Account Setup
  6. Search Configuration
  7. Roles, Privileges, and Profiles
  8. Data Asset Access and Publication Management
  9. Masking Sensitive Data
  10. Monitoring Enterprise Data Preparation
  11. Backing Up and Restoring Enterprise Data Preparation
  12. Managing the Data Lakehouse
  13. Schedule Export, Import and Publish Activities
  14. Interactive Data Preparation Service
  15. Enterprise Data Preparation Service

Enterprise Data Preparation Administrator Guide

Enterprise Data Preparation Administrator Guide

Enterprise Data Preparation Overview

Enterprise Data Preparation
Overview

With the advent of big data technologies, many organizations are adopting a new information storage model called data lake to solve data management challenges. The data lake model is being adopted for diverse use cases, such as business intelligence, analytics, regulatory compliance, and fraud detection.
A data lake is a shared repository of raw and enterprise data from a variety of sources. It is possible to store large volumes of structured and unstructured data from various enterprise systems within and outside the organization. Data in the lake can include raw and refined data, master data and transactional data, log files, and machine data.
Enterprise Data Preparation
helps you derive more value from the data sources such as Hive, HDFS, Microsoft Azure data warehouse using a native connector, and Microsoft SQL Server using a JDBC V2 connector, and make data available to all users in the organization.
Organizations are looking to provide ways for different kinds of users to access and work with all of the data in the enterprise, within the Hadoop data lake as well data outside the data lake. They want data analysts and data scientists to be able to use the data lake for ad-hoc self-service analytics to drive business innovation, without exposing the complexity of underlying technologies or the need for coding skills. IT and data governance staff want to monitor data related user activities in the enterprise. Without strong data management and governance foundation enabled by intelligence, data lakes can turn into data swamps.
Enterprise Data Preparation
is a collaborative self-service big data discovery and preparation solution for data analysts and data scientists. It enables analysts to rapidly discover and turn raw data into insight and allows IT to ensure quality, visibility, and governance. With
Enterprise Data Preparation
, analysts to spend more time on analysis and less time on finding and preparing data.
Enterprise Data Preparation
provides the following benefits:
  • Data analysts can quickly and easily find and explore trusted data assets within the data lake and outside the data lake using semantic search and smart recommendations.
  • Data analysts can transform, cleanse, and enrich data in the data lake using an Excel-like spreadsheet interface in a self-service manner without the need for coding skills.
  • Data analysts can publish data and share knowledge with the rest of the community and analyze the data using their choice of BI or analytic tools.
  • IT and governance staff can monitor user activity related to data usage in the lake.
  • IT can track data lineage to verify that data is coming from the right sources and going to the right targets.
  • IT can enforce appropriate security and governance on the data lake
  • IT can operationalize the work done by data analysts into a data delivery process that can be repeated and scheduled.