Book description
Business executives today are well aware of the power of data, especially for gaining actionable insight into products and services. But how do you jump into the big data analytics game without spending millions on data warehouse solutions you don’t need? This 40-page report focuses on massively parallel processing (MPP) analytical databases that enable you to run queries and dashboards on a variety of business metrics at extreme speed and Exabyte scale.
Because they leverage the full computational power of a cluster, MPP analytical databases can analyze massive volumes of data—both structured and semi-structured—at unprecedented speeds. This report presents five real-world case studies from Etsy, Cerner Corporation, Criteo and other global enterprises to focus on one big data analytics platform in particular, HPE Vertica.
You’ll discover:
- How one prominent data storage company convinced both business and tech stakeholders to adopt an MPP analytical database
- Why performance marketing technology company Criteo used a Center of Excellence (CoE) model to ensure the success of its big data analytics endeavors
- How YPSM uses Vertica to speed up its Hadoop-based data processing environment
- Why Cerner adopted an analytical database to scale its highly successful health information technology platform
- How Etsy drives success with the company’s big data initiative by avoiding common technical and organizational mistakes
Publisher resources
Table of contents
- 1. Introduction
- 2. Where Do You Start? Follow the Example of This Data-Storage Company
- 3. The Center of Excellence Model: Advice from Criteo
- 4. Is Hadoop a Panacea for All Things Big Data? YPSM Says No
- 5. Cerner Scales for Success
-
6. Whatever You Do, Don’t Do This, Warns Etsy
- Don’t Forget to Consider Your End User When Designing Your Analytics System
- Don’t Underestimate Demand for Big-Data Analytics
- Don’t Be Naïve About How Fast Big-Data Grows
- Don’t Discard Data
- Don’t Get Burdened with Too Much “Technical Debt”
- Don’t Forget to Consider How You’re Going to Get Data into Your New Database
- Don’t Build the Great Wall of China Between Your Data Engineering Department and the Rest of the Company
- Don’t Go Big Before You’ve Tried It Small
- Don’t Think Big Data Is Simply a Technical Shift
Product information
- Title: The Big Data Transformation
- Author(s):
- Release date: November 2016
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491964736
You might also like
book
Managing Data Science
Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key …
book
Practical Big Data Analytics
Get command of your organizational Big Data using the power of data science and analytics About …
book
Big Data For Dummies
Find the right big data solution for your business or organization Big data management is one …
book
The Evolving Role of the Data Engineer
Companies working to become data driven often view data scientists as heroes, but that overlooks the …