Big Data in a Company – How to Start

30 January 2019 | Piotr Ferster | big data development

An uncomplicated initial project allows you to see how Big Data can solve business problems with relatively low risk. Learn what steps should be taken when implementing solutions based on large data sets and how to avoid questionable moves.

From the article you will learn:

  • how to prepare a company to implement Big Data solutions;
  • how to make first steps in Big Data projects;
  • about the application of data sets in practice;
  • about the possibility of data problems.

After reviewing numerous examples of the use of large data sets on the Internet, you can be impressed by their size and the potential gathered in one place. What is more, you can even employ Big Data solutions to create a competitive advantage. However, it is not so easy... Before the practical application of data sets and starting a project using Big Data in an organisation, you need to know the awaiting traps an loopholes. Below you can find a small guide on how to use the method of transferring large amounts of data in the industry.

Getting a company ready for using Big Data

To start using large data sets in production, it is worth taking into consideration actions such as:

  1. Finding the right perspective for the use of Big Data . It is very important to carefully analyse the needs of an organization, identify the ways to fulfil them with big data, and give up the chase after the existing trends for purposes that do not offer a real business advantage.
  2. Careful planning for the adoption of large data sets. At the very beginning it is worth to consider a small-scale project activities, and then test the first Big Data implementation within it. The correct and well-proven sequence of activities is: data collection, simple algorithms testing, and then trying more bold solutions.
  3. Considering the time needed for the challenges related to information management. You should try to obtain a deep and multi-level understanding of the data and employ the necessary number of engineers or technologists for the project.

Beginnings of using Big Data

To prepare for a Big Data project, you should take the right approach. First and foremost, do not become obsessed with the Big Data idea, hurrying to get the necessary budget, which results in not unlocking the full potential of your data sets. It is worth to create a solid foundation for new processes related to the generation and analysis of information. The steps presented below are characteristic of activities focused on matching the business with the IT requirements, and of activities aimed at improving the quality of digital products in a company. The first steps with Big Data are contained in the following points:

  • Big data research and determining what strategic goals a company can achieve thanks to huge data sets;
  • Consulting with the engineering management department and performing actions focused on understanding the production processes based on the use of dynamic information;
  • Obtaining a confirmation from the engineers that the implementation of tasks under Big Data is needed;
  • Convincing the management board to run a test project.

Simple Big Data projects for the start

You cannot test the abilities of large data sets on complex tasks from the very beginning. Software companies should start with a simple project – trying, for example, to achieve a stable quality when implementing a new application or system. A simple initial project allows you to see how big data can solve the emerging problems with potential business risk and further investments. This, in turn, may positively influence the opinion of the management on Big Data and encourage them to continue to spend time and financial resources for large data sets, but within the framework of more important analytical projects. Given the fact that an excessively complex and risky initial project, for example in the form of a reorganisation of the entire software development process can have a lasting effect on its further proper operation.

If we are talking about data within a more globally-operating project, you should always divide the information sets into smaller stages of their ”absorption” and approach them on an individual basis. The following phases for the challenge related to big data are promoted here:

  • Data aggregation;
  • Use of simple analytical algorithms;
  • Moving to more sophisticated analytical methods;
  • Gradual automation of production management.

Possible dangers and problems

Immediately after the start of an actual project involving the adoption of large amounts of data, some difficulties may occur (say, from the project management side). That is why it is worth to remember about the management challenges that may arise when developing software using large sets of information, including:

  • Lack of internal technical skills;
  • Lack technologists with analytical skills (Big Data) in the team;
  • Not taking into account new technologies in the processes.

Safe implementation of Big Data solutions

Big Data can prove to be a very helpful tool in the company's long-term strategy. You should remember, however, about possible difficulties, and above all – about gradual implementation of the steps described above. Only a gradual implementation of Big Data in the company and its structures can end successfully. Otherwise it is easy to put it at risk at the initial stage of the project. This is especially the case when your Big Data adventure begins with a key project with a huge reach. After choosing the right concept for the use of large data sets in the organisation, and consistent implementation of the ”small steps” plan, the benefits of implementing Big Data solutions will probably prove to be a great benefit for the company.

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