Data Strategy Development Helps in Aligning The Business Goals

In every business, especially that involves financial transitions, there should be a clear and well-defined data strategy. That is what you see in modern business. When you have a well-defined data strategy it will help you a lot in aligning it with your business goals. Unfortunately, a lot of companies strive to be data-driven but all of them are not as successful as they should have been.

Experts suggest a lot of reasons for this failure but one of the most significant reasons that most of the companies are found struggling with big data is their short term focus. That means, instead of strategically looking at the data they are more focused and interested in carrying out one-off projects.

The experts suggest that in order to avoid this, the companies must use data from a different perspective. They advise that:

  • Data should not be used just to accomplish a singular goal
  • They must broaden their outlook
  • They must have specific business goals and
  • They must develop a comprehensive strategy.

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All these will help them to achieve their broader business goals. This principle and process should spans across all departments including the network of partners that they might have. This will help them all to move forward with the big data and at the same time grow along with it.

Data Strategy Development

Start slow but be steady

When you develop a data strategy for your business, make sure that you start slow and move ahead steadily. The best way to start with is to consider one specific business problem and then expand on it. This will help you significantly to move ahead onto your other data-driven efforts. The process involves three steps:

  • Identify one specific business problem
  • Resolve it with data and then
  • Expand on the solution thus created to address the other issues

This simple process will help you to break up the overwhelming effort of using big data into chunks that are bite-sized! It will eventually help you to build upon easily in the future.

The fundamental elements

Big data clearly is the big thing for modern businesses and has become the most fundamental element by its own rights. Whether it is a business that deals with tangible products or financial services such as or any other, the success of any business today will largely depend on the ability of the business to harness and use big data in a big way.

The basic thing about data strategy is to follow the 3 V’s of big data. By using the data and analytics companies can gain valuable insight that will help them to make important business decisions and inform their clients about it as well in a much better way. The big data strategy is adopted by almost all segments of the business including but not limited to:

  • Financial services
  • Business marketing
  • Technology companies
  • Health care to name a few.

Such extensive adoption of big data redefines the competitive landscape of modern business. According to research, it is found that 89% of companies believe that they are well off with their well-developed analytics and data strategy in place. It is believed that those businesses that do not follow this specific process run at a risk of losing their competitive edge over the others in the market. With the help of the widely adopted big data analytics businesses can:

  • Inform better investment decisions and
  • Ensure consistent returns.

In combination with big data, the businesses can also use algorithmic trading methods along with the vast historical data that comes with complex mathematical models. This will help them to minimize their efforts and maximize portfolio returns.

With such continual adoption of big data, it does not need any further explanation or proof that it will certainly change the landscape of modern business. However, big data strategy does not have its apparent benefits only. It poses significant challenges with regard to the ability of big data to capture the ever-rising volume of data.

The 3 V’s of big data

The 3 V’s of big data form the foundation of this strategy that will ensure a big success for any business, financial or any other. These are:

  • Volume of data
  • Variety of data and
  • The velocity of data.

With the increasing competition faced by modern businesses as well as the ever-changing consumer needs and regulatory constraints, businesses now should lookout for new ways so that they can leverage technology to increase efficiency.

Out of the three fundamental aspects of big data strategy, companies can use specific aspects of it for their competitive advantage depending on the industry.

Categories of big data

Ideally, big data can be categorized into two groups: unstructured or structured data.

  • Unstructured data is the information that does not fall into any pre-determined model because these are unorganized. This includes data collected from different social media sources. This type of data helps businesses to get valuable insights into customer needs.
  • Structured data, on the other hand, consists of the information that is already managed by the company with the help of different spreadsheets and relational databases and spreadsheets.

It is only when different forms of data are actively managed by the company it will be easy for it to inform better business decisions to its clients.

However, with the increasing volume of data in the market, it poses a bigger challenge for companies to arrange and use it for their beneficial purposes. Apart from the challenges of the vast historical data, there also the need for managing the ticker data by the businesses, especially the capital and banking sector of business.

Similarly, investment companies and asset management firms are required to manage voluminous data. This will help them to make sound investment decisions as well.

In addition to that, even the insurance companies and retirement firms will also be befitted with big data strategy as they will be able to access their past policy or claims and other information to ensure that they have an active and effective risk management process in place.

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