Chapter 1. Integrated Analytics: Platforms and Principles for Centralizing Your Data
Abstract
Data centralization merges different data streams into a common source through unified variables. This process can provide context to overly-broad metrics and enable cross-platform analytics to guide better business decisions. Investments in analytics tools are now paying back a 13.01:1 return on investment (ROI), with increased returns when these tools integrate with three or more data sources. While the perks of centralization are obvious in theory, the quantity and variety of data available in today’s landscape make this difficult to achieve.
This report provides a roadmap for how to connect systems, data stores, and institutions (both technological and human). Learn:
- How data centralization enables better analytics
- How to redefine data as a vehicle for change
- How the right BI tool eliminates the data analyst bottleneck
- How to define single sources of truth for your organization
- How to build a data-driven (not just data-rich) organization
Introduction
Data is a valuable asset and, as a result, companies are more hungry for data than ever before. New products address that need by providing metrics on every step of a sales pipeline (from social media and marketing, to website traffic, sales and product usage, through customer support). The increase in software as a service (SaaS) products contributes to the data firehose—by 2016, the use of cloud services for business processes ...
Get Integrated Analytics now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
