Estimated reading time: 2 minutes, 36 seconds

Analyzing and Reporting

analytics resultsA while back, in December, 2010, we covered How Business Analytics is Being Delivered in the EDI World. Lot of water over the dam since then, so let's take a look! Business intelligence / analytics coupled with data aggregation are not new terms. They have depended directly on the business system (like SAP) hence indirectly on the EDI system. They go back before EDI: a lot of them were once called “Decision Support Systems.”

So what do we focus on with Business Intelligence? A common list includes: (1) Customer Behavior (what your customer has done previously is an indication of what the customer might do in the future), including data like does customer buy at store, over the phone or on the Internet; (2) Sales and Marketing Research (all kinds of external data); (3) Financial Analysis (includes budget analysis and “spend analysis”); (4) Procurement; (5) Supplier Relationships.

TechTarget has put together a guide to Big Data tools, trends and best practices. They emphasize the importance of having a strategy to use the tons of data available to identify trends, detect patterns and glean other valuable findings. Software by itself won't cut it. You need analytical processes and skilled people to carry out an effective big data analytics initiative.

“Search Cloud Computing” from Tech Target defines Big Data as follows: a general term used to describe the voluminous amount of unstructured and semi-structured data a company creates -- data that would take too much time and cost too much money to load into a relational database for analysis. Although Big data doesn't refer to any specific quantity, the term is often used when speaking about petabytes and exabytes of data. A primary goal for looking at big data is to discover repeatable business patterns. It’s generally accepted that unstructured data, most of it located in text files, accounts for at least 80% of an organization’s data. If left unmanaged, the sheer volume of unstructured data that’s generated each year within an enterprise can be costly in terms of storage. Unmanaged data can also pose a liability if information cannot be located in the event of a compliance audit or lawsuit. Big data analytics is often associated with cloud computing because the analysis of large data sets in real-time requires a framework like to distribute the work among tens, hundreds or even thousands of computers.

A term from the late 1980's that has gotten dusted off, spruced up and adopted by the Cloud is “Data Warehouse”. defines it simply as a a large, centralized collection of digital data gathered from various units of an organization.

Another older term that fits into the Cloud perfectly and pops up a lot is Data Mining. calls it the process of collecting, searching through, and analyzing a large amount of data in a database, as to discover patterns or relationships: the use of data mining to detect fraud.

Lot of opportunities to collaborate with partners like suppliers, vendors, customers

Want to safely jump into this amazing new world? Best finding an experienced partner for help. Check out Techdinamics. For a robust link to vendors, see the EDI Tool Box.
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