Database Management Strategy and How Has It Evolved
Though there are long-term and heavy investments in data management, experienced DBAs skilled in database administration and management state data issues at multiple companies continue to increase. One prime reason being that data has been conventionally perceived to be an aspect of any technological project. And it has not been treated as an asset for the corporate.
Consequently, the general belief is that the conventional efforts for database planning and traditional application were adequate to take care of continuous data management issues. Corporate data has increased both in subject and size. This means to address this data, a strategy for its effective management needs to be devised. However, the unfortunate part is some companies still struggle with the thought that corporate data needs an extensive strategy. There is no shortage of thinking when it comes to road maps and strategic planning of companies. To many businesses, these efforts are just a novelty.
Experienced DBAs in database administration and management agree that some companies whose strategic plans for data management generate minimal tangible results for them. They waste time with unnecessary documentation and meetings. A successful data management strategy plan will detect realistic goals with a road map that offers precise guidance on how to get the job done effectively.
Data strategy- does it solve problems?
When it comes to real-life cases, let us examine how data strategy worked for an organization when they set out to develop one.
Consider this example of a database consulting team that assists a large bank in creating a data strategy. At the outset, the project head found it challenging to get the bank’s VP to consider the requirement and importance of the data strategy. The reason?
The bank was already doing quite well in the market, with its costs and revenue managed well. Even the individual units in the business and tech groups were excellent when delivering solutions against their commitments. To the credit of this bank, the data strategy was not complacent. The bank’s management always looked out for ways to boost the productivity of their employees and reduce the ongoing costs. There was a wide array of metrics and other key performance indicators or KPIs for assessing the IT performance and the total costs of ownership and business benefits.
The thought of establishing another road map or plan for addressing the issue was not fully comprehended, and the suggestion was met with pushback. The VP tendered his explanation with some questions, like they have multiple projects being executed at a specific time. They were good when it came to managing the data storage requirements, their application and analytic platforms, software costs, and managing the project budgets. Each project detected the resource and the staff costs, and the bank never moved ahead without the company covering the costs, so why does it need a data management strategy, and what problems will be resolved?
Naturally, with everything going right for the bank, the VP had to know how the data management strategy could have made a positive difference to the bank’s performance. To answer these questions, you need to understand how data was established and used in the past to compare how it is created and used in the present.
Data management- the past and the present
In the past, as experts from esteemed data administration company RemoteDBA.com observe, data was generally perceived as a result of a business process or activity. It has less value after the completion of the process. There might have been about a few applications that had to access this content for a follow-up like special reports, audits, customer service, and more, but they were generally rare activities. If you take a look at the modern businesses of today, the whole scenario is so different. The data of a business has tremendous value, and the results of analytics and reports have given businesses a lot of power. It is quite common for an application’s data to be shared and distributed among several other IT systems.
The value of information and data has tremendously evolved over the last two decades, and users of an organization now recognize it. Some companies have adjusted their general approaches to capture, share, and manage corporate assets of data. Their behavior again reflects an underlying and outdated belief that data is just a result of an application’s byproduct. Companies today should create data strategies that sync in with the realities of modern times. To establish such an extensive data strategy, organizations need to account for present technology and business promises while paying attention to new objectives and goals.
The need for a data strategy
Going back to the bank’s story and its VP’s concerns, it was surely not difficult to comprehend. He has spent a lot of time wading through proposals for projects, and his committed staff was greatly emotional about them. In several cases, the project’s objective was to deliver perfection and convert something that was already working well into something better, faster, or stronger.
The VP understood the finite resources and budget scenario whenever newly approved projects would take away funding from other requests. His philosophy was simple, and that was he wanted to know how an idea was more crucial over the items that already were on the bank’s priority list. The skilled DBA consultants were ready for this discussion as the problem was not associated with the premise or the project’s value in question. The problem was the approach that every project took and its activities. Every activity addressed the data requirements completely different from the other without awareness of costs and efforts that overlapped with one another.
On examination and studies, the result that the DBA consultants discovered was duplicate data along with processing overlaps with a little awareness that every project was replicated the earlier work. They concluded that there was nothing in place to support the continuing, collaborating, and sharing diverse data methods across diverse systems and projects in the bank. This is where the bank failed.
Therefore, in conclusion, it can be safely said that this is where a database strategy comes into play for modern businesses. It is no longer a result of a process but a critical tool to make informed corporate decisions for progress and growth.