Data is changing everything. Many industries today are being fundamentally transformed through the accumulation and analysis of large quantities of data, stored in diversified but flexible repositories known as data lakes. Whether your company has just begun to think about big data or has already initiated a strategy for handling it, this practical ebook shows you how to plan a successful data lake migration. You’ll learn the value of data lakes, their structure, and the problems they attempt to solve. Using Zaloni’s data lake maturity model, you’ll then explore your organization’s readiness for putting a data lake into action. Do you have the tools and data architectures to support big data analysis? Are your people and processes prepared? The data lake maturity model will help you rate your organization’s readiness. This report includes: The structure and purpose of a data lake Descriptive, predictive, and prescriptive analytics Data lake curation, self-service, and the use of data lake zones How to rate your organization using the data lake maturity model A complete checklist to help you determine your strategic path forward

Organizations across many industries have recently created fast-growing repositories to deal with an influx of new data from many sources and often in multiple formats. To manage these data lakes, companies have begun to leave the familiar confines of relational databases and data warehouses for Hadoop and various big data solutions. But adopting new technology alone won’t solve the problem. Based on interviews with several experts in data management, author Andy Oram provides an in-depth look at common issues you’re likely to encounter as you consider how to manage business data. You’ll explore five key topic areas, including: Acquisition and ingestion: how to solve these problems with a degree of automation. Metadata: how to keep track of when data came in and how it was formatted, and how to make it available at later stages of processing. Data preparation and cleaning: what you need to know before you prepare and clean your data, and what needs to be cleaned up and how. Organizing workflows: what you should do to combine your tasks—ingestion, cataloging, and data preparation—into an end-to-end workflow. Access control: how to address security and access controls at all stages of data handling. Andy Oram, an editor at O’Reilly Media since 1992, currently specializes in programming. His work for O'Reilly includes the first books on Linux ever published commercially in the United States.