You Have Just Built A Gorgeous Data Warehouse – Now What?

From Data Warehousing to Analytic Solution

The concept of data warehousing started at IBM Labs back in the late 1980s to provide an architectural model for storing, sorting, and accessing data from various operational systems to support decision making in large, complex organizations.

Data warehousing evolved into data mining and, further, into business intelligence. As technology progressed, solutions became faster, more reliable and offered greater computing power to manipulate the data. The outcome of this manipulation, from sorting and sifting to slicing and dicing, is presented to the user in all sorts of reports.

With today’s advanced technology, reports became much more user-friendly than the old fashioned, dreaded stacks of small print tables of the past. Today, reports offer colorful, graphic elements, from pie charts and bar graphs to maps and color–coded, three–dimensional tables that make them so much easier to examine and from which to benefit.

Interactive reports – dashboards with various drill–down capabilities, make them even more user-friendly, providing users with the means to dissect and evaluate situations.

Still, with all the available automation, the user, typically a skilled analyst, has to actively scrutinize the reports to arrive at meaningful insights and derive actionable conclusions.

Reporting vs. Analysis

It is important to distinguish between reporting and analysis, as both draw from collected data, sometimes the lines between these two tend to blur:

  • Reporting is the process of extracting information from your data warehouse and organizing it into convenient informational summaries that help track and monitor your business and its performance. Your reports are an excellent tool to raise questions about your business’ performance.
  • Analysis is the process of actually using these reports – exploring the information to extract meaningful insights that help understand the business and pinpoint problem areas or untapped opportunities. These insights can be translated into actions to improve the faulty processes.

Analysis is an excellent tool to find answers about your business performance.

In summary, reporting provides numbers that show you what is happening, while analysis focuses on explaining why it is happening and how you can act on it.

Reports are essential for analysis. The analyst needs the data to be sliced and diced in a way that highlights trends and drifts, to scrutinize it and extract actionable insights. However, without profound analysis, reports have very little value beyond mundane managerial tasks and as a reference in management presentations to underscore various facts and events of the past.

So, you’ve just built a gorgeous data warehouse for your organization.

Data from a variety of sources is collected and assembled in one place. This is a great start! Now, to achieve the full benefit of your investment you ought to think about the next step of your business analytics solution.

There are two ways you can handle the analysis of your data:

  1. You may employ teams of skilled analysts that will study the reports, carefully examine them to find trend breaks and unexpected changes, draw conclusions about threats and opportunities to your business, and devise actions to be taken.
  2. Alternatively, you may opt for an automated analytics solution that can automatically apply heuristics, business rules, historic, geographic, and demographic segmentations to pinpoint areas of problem that require action and areas of opportunity that should be leveraged. You will still need the human touch at the end of the process, to take advantage of these distilled insights, but a much smaller and more focused and strategic team of professionals that could skip the mundane and take full advantage of the lucid insights revealed by the automated analysis.

The more common, traditional approach, is a wide variety of available reports combined with a large group of analysts to make sense of them. More novel is the automated route, which is typically combined with a smaller, proficient team that cuts the chase and drives action.

There’s a lot that can easily be automated – organizing, consolidating, and summarizing. More sophisticated automated analysis also compares, examines and interprets the data, to find correlations and inter-dependencies between events. The more high-level your automation, the more top-notch your team of analysts and subsequently, the quality of your business management.

How to Make the Most Out of Your Data

To make the most out of your data, you definitely want to add automation to your business intelligence. Having an army of low level data ‘analysts’ sift through the data to sort, format, and organize it, is quite a waste of time and extremely prone to error.

The more advanced automated solutions will truly boost your business performance. However, you want to make sure you’re carefully selecting a solution that was developed by amalgamating domain expertise of your specific field of business, as only such a solution could not only replace an army of analysts, but even do a significantly better job on 90% of analytical tasks.

For the 10% of most complex and out of the ordinary situations, you still want to employ a handful of highly sophisticated analysts that will not waste their time and repetitious, tedious tasks but rather focus on complicated situations that are crucial for the business.

Congratulations on your new data warehouse! Now go on, and keep improving your information technology to make all this available data we can collect these days, work to your benefit.