The State of Data and Analytics



Companies have realized the value that they can get from analyzing their data and acting upon that analysis. In today’s world, knowledge is everything. In this case, however, information is everything. If you have the right information and data, you may succeed in maintaining your business at float or even more. In order for a company to be successful, it has to make good use of the available data and information. The bad news is that companies, enterprises and organizations are overwhelmed by the flood of information. And if they can effectively analyze the information they can get enough data to act upon.

Business Intelligence has come to a point where the entire decision making process is depending on it. Many enterprises have a business intelligence framework integrated, but there are few who use the tools correctly. Companies can find themselves in this critical position due to the usage of standard techniques, technology and tools that have been mainstream in BI and DW even before the Big Data flood. But a significant increase in the volume, variety and velocity of the data stream has been noticed during the last several years. A few years ago, companies were integrating data from internal operational systems, but in the last years, they have expanded to data interchange with customers, managers, partners, suppliers, prospects and stakeholders.

Businessmen have now considerably more available data at their disposal. But even with all this data, there is still an information gap. This is due to the data being stored in data silos and spreadsheets. This is called the data superglue phenomenon. This is very frustrating for the business managers and leaders. It translates into lost opportunities for a better management and growth over the enterprise’s revenue and profits.







What is holding the Enterprises back?



The last couple of decades have been a time of development and improvement for business intelligence and data warehouses. They have matured, enabling companies the ability to store and integrate data from internal operational systems as well as from external data sources. A typical technical architecture includes servers, storage units coupled with DB, data integration and BI tools. The capacity of these systems has expanded over the years, but most of the systems are still all-purpose systems and are built to handle transactional, operational and Business Intelligence applications. The data flood is putting these systems under a lot of stress. And this is if we assume that these all-purpose systems can meet the requirements of BA (business analytics) that companies need nowadays.

The typical data architecture is actually quite simple. Or at least it seems simple. It involves creating a data warehouse where all the data is integrated. Then data marts or OLAP cubes are built for specific business analysis. This architecture has been effective for a long time, but most of the companies nowadays are unsuccessful in keeping up with the data flood. The processes requires skills and technical knowledge. It is also time consuming and labor intensive.

But even if the all-purpose systems encounter problems with the huge data streams, this doesn’t mean that technology is not evolving. Business Intelligence has evolved a lot during the last decade. Let’s not forget that the “Business Intelligence” term has appeared in the ‘50s. Now, the technologies that have been used in BI processes – BI tools and data sets - have evolved to a point where they will take this domain to the next level.

And the next level is considered to be Business Analytics. If you take these processes, along with the technical innovations concerning servers, speed, memory, bandwidth, storage, storage speed and many others, the BI domain will be even more efficient in the close future.

The question is why companies are still falling behind with all these improvements. The answer is: because these processes are also time consuming, labor intensive and require technical skills from within the company. These processes are required to take place in accordance with the actions of technical staff. However, the trend is to give access only to the key personnel – the business manager, the departmental management, etc. And it is taking too long for non-technical staff to learn and adapt to the “technical improvements” and data flood.

Business Analytics is a great tool for those who know how to use it and some even say that BA exceeds Business Intelligence. In my opinion, we’re currently going through a transition period from BI to BA. I don’t know how much this will last, but for the next years I think the right thing to do is to complement the BI processes with the BA processes – Spreadsheet, dashboard, reporting tool for the structured data and OLAP and data-mining for the unstructured data. A complementary technique just seems like the right answer.