Making Business Intelligence & Cognitive Simpler

Today’s world is shifting rapidly towards Business Intelligence (BI) and Cognitive.

Yet when it comes to these innovations, we all too often focus narrowly on the destination while failing to adequately consider the transformation journey.

However, it’s the decisions that are made on that journey that will determine the profitability of the result. So while BI and Cognitive are transformational for the organization, the fact that it doesn’t come from an app store can often be problematic.

Data – The New Natural Resource

Today, when it comes to Business Intelligence and Cognitive strategies focus needs to be on the methods as well as on the goals.

First and foremost, this means addressing the question about how to persist, ingest, and analyze data. Ignore any underlying data issues severely compromises and the impact of any strategic innovation.

It's not hard to find companies that have built seemingly strong Cognitive, and BI platforms only to then fail to reap any benefits because the underlying data issues weren't addressed.

Why is this the case?

Connectivity is usually the most visible, and usually the easiest, requirement to address. Yes, in today's world, machines connect to machines and applications connect to applications but connectivity is simply the means of communication; it is only the pipe through which a natural resource flows.

The natural resource in the Cognitive and BI world is data.

Addressing connectivity and then ignoring issues of persisting, ingesting and analyzing the raw material - data - is an example of building a road or a bridge to nowhere.

Successful BI and Cognitive strategies are 'data first.' It’s only useful to have new, fast, and flexible ways to run your business if you know what you actually need to accomplish. Without data, there is no natural resource to utilize.

This being the case, how you address data integration and management is mission critical to the success of any BI or Cognitive transformation.

If you’re already deploying smart meters, selling smart appliances, creating recipes based on available ingredients, or assisting Doctors, Oncologists, and Lawyers, but you’ve overlooked the data issues, it’s not too late.

Make Data Simple

The need is to Make Data Simple. The easiest way is to utilize a data platform or layer that sits between the network and the system of record applications, and those used to manage the business like systems for customer relationship management, performance optimization, financial management, etc. that are situated on “top” of them.

The latter group requires information from the former in order to perform effectively (for instance, a CRM system can’t assist the call center representative without the information relating to the customer’s activities, and ideally sentiment about those activities) so it stands to reason that the better the quality of that information and the faster it becomes available, the better the performance of the business and its people.

Data Platforms are available that enhance existing technology investments; they don’t replace them. Also they increase Return on Investment across the board.

The Data Platform

What is ‘under the hood’ of a data platform? What should the organization expect it to do? How should it be expected to work? What value will be accrued from using it?

Here are my thoughts of features and functions that organizations a data platform should have in order help drive an organization to success:

• Collecting data in any format or type from any source in your environment (structured, unstructured, semi structured, or otherwise).
• Enriching data from any additional externally available database or application.
• Enabling self-service access to well-governed data, bringing together the different data repositories under a common umbrella.
• Assignment of amounts or values to the data if that is desirable/appropriate, as well as the correlation, consolidation, and aggregation of different types of data from any of the recognized data sources.

There is more. It’s also critical to have the ability to audit and report data-related processing, ensuring in the process that there’s no inappropriate usage. Also, the management of master data is important.

Data platforms should also be able to help consolidate multiple other data persistence and ingestion platforms and/or other applications while still ensuring vendor independence. Thus the platform should embrace and utilize Open Source where appropriate.

Plus, the platform should address data quality and support a governance methodology and confer a degree of infrastructure future proofing to protect and extend RoI on existing investments.

Four other characteristics are particularly important too.

1. The ability to leverage data via either bulk or real-time processing as required.

2. A system that is quick to implement and easy to configure meaning the ability to dynamically support and even drive your ability to respond to changing market conditions or perhaps even changes in the weather!

3. Support for complex data needs is another consideration. Business Intelligence and Cognitive always benefit from as much data as can be delivered. The right data platform offers the capability to collect and process complex data types, even binary machine logs via simple configuration.

4. And a final point is future proofing. Your business will likely expand over time to include more data sources which often brings complicated data collection into the Business Intelligence or Cognitive project scope.

Ignoring the BI and Cognitive transformation will ultimately be suicidal for the organizations. The same can be said of ignoring fundamental questions of data architecture, integration, and management.

Making the natural resource of data simple and accessible to the organization's world is critical to the success of any BI or Cognitive transformation journey.