From The Editor | October 6, 2010

5 Tips: How To Transform Data Into Business Intelligence

Webinar: Cloud 101

Here is an interesting column that landed in my inbox a few weeks ago, sent by Digitiliti, a vendor that develops advanced Information Management solutions. As more and more data flows through your customer's networks, that means more and more information stored in each business. So why not use that information to help your customers grow? Want to know how? Read on.

Business intelligence and decision support systems are traditionally built on information derived from structured data found in databases and data warehouses. But with the amount of business value hidden in vast resources of unstructured data, businesses need a new paradigm: Operational Business Intelligence. Operational BI systems are based on giving more people in an organization faster and easier access to more information to make better business decisions at the operational level. A highly effective method to accomplish this is by implementing a comprehensive data management system that brings structure to unstructured data to unlock its business value.

Here are five key points to consider that will enable companies to extract Operational Business Intelligence from obsolete, unstructured data:

  • Eliminate Multiple Point Solutions with a Single Management Application
    The cost of deploying and managing multiple point solutions can easily outweigh the business value of information locked inside unstructured data stores. The preferred solution is to deploy a single, centralized application that can bring order to unstructured data with capabilities such as continuous data protection, global deduplication, content indexing, metadata management, data encryption, life cycle policies and more.
  • Provide Simple to Use Client Tools
    A key to delivering Operational Business Intelligence is providing clients with simple-to-use tools that enable them to search and access data that has been captured and structured to improve business processes and decisions at the user level.
  • Capture Metadata at the Time of Creation
    Adding structure to unstructured data begins with capturing and leveraging object metadata. Capturing metadata when objects are created ensures quality of the data and that objects are accurately indexed and managed throughout the complete data lifecycle.
  • Centralize Management for Enterprise-wide Policy Enforcement
    It is critical for companies to use a centralized management application – rather than a handful of point solutions – that can enforce data retention and protection policies for the lifecycle of the information, including end-of-life-cycle data deletion. Centralizing and automating data retention policies provides quantifiable ROI for companies by reducing audit time, improving regulatory compliance and ensuring better litigation support and eDiscovery with lower costs.
  • Organize Files and Data Objects by Business Value Rather than Location
    Businesses derive no value from files and information objects that are organized by traditional file systems by name, size and directory. Instead they need a system that transforms files and email messages into unique Information Objects, then organizes those objects by their inherent meaning and value to the organization for the purpose of capturing operational intelligence and economic benefit from the wealth of content created daily.
Courtesy of Digitiliti