8 Best Practices for Big Data Project Management

With the emergence of Big Data, companies are busy managing more and more data. It takes a lot of skills to manage databases and information. Most importantly, it takes the right approaches. Here are some good practices for managing Big Data.

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1. The digital transformation of business processes

The important thing in Big Data management is not really the volume of data. Priority must be given to the digital transformation of business processes. The size of the data volume that digital business activities produce is impressive, but the bottom line is that in more technical professions, Big Data is based on Volume, Speed and Velocity of data.

Big Data cannot be considered solely in terms of the volume of data. The data itself has a much greater economic potential. The scope of the current digital transformation should not be minimized. Big Data represents the visible part of the transition from the industrial world to the digital world.

We are in an era of digital democratization where more and more people are connected to the Internet. The digitization of businesses is adding to the number of people who have ever more diverse means of accessing the Internet. It is possible to connect using a large number of media. The increasing number of digital activities generates data.

To this volume, we must add all the connected objects which are also in full expansion. The Big Data is only a result of this state of affairs and not the primary cause. It is therefore necessary to start a Big Data project by seeing the volume of data as a consequence. The important thing is to focus on how to digitize business processes instead of focusing on the amount of data produced.

2. Set clear objectives

To set up Big Data projects, you first need a clear idea of why the project is being set up. The data and the means are there. It remains to be understood that the purpose of data analysis is to find solutions that lead to greater profitability and competitiveness for the company. 

When the objectives are well defined and the business problems to be solved are well identified, a Big Data project has every chance of success.

3. Encourage collaboration

The success of a Big Data project is largely due to the collaboration between business and technology teams. It is a mistake to consider the Big Data project as a project that does not require the involvement of several functions. Rather, the Big Data project should be seen as a way to improve business performance, which involves several teams within an organization.

The more employees involved in using the information from the data analysis, the more they will be able to collaborate on the project and make the applications more efficient and usable.

Starting a Big Data project without the full support of all stakeholders can lead to failure. Well-defined objectives must be clearly explained to all key stakeholders. That way, everyone is on the same wavelength. Big Data always raises a few doubts, and some business leaders always favor instinct. So it is important to maintain the dialogue while promoting the benefits of the project.

4. Choose the appropriate equipment

Traditional data management involves centralizing data processing and storage on a central server within a client/server architecture. This type of management has great difficulty adapting to the phenomenon of megadata. To succeed in the Big Data project, it is no longer necessary to centralize the storage in a single server but rather to distribute this storage on several computers.

This technological approach is well illustrated by Hadoop. It is a software implementation widely used by most companies.

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5. Ensure data availability

When setting up a Big Data project, it is important to ensure that the data is available to those who need it. By properly targeting the members of the company who are stakeholders and making the data available to them, it becomes easier to convince them of the relevance of the analysis carried out.

Companies often operate in such a way that each department has its own data. Each set of information is contained in a silo to which other groups in the organization do not have access. The Big Data project will only be truly useful if all organizational data is available at all times to those who need it. The relationships and patterns that emerge can then be fully exploited.

6. Analyze only what is usable

The main objective of Big Data is to generate information that can be used by the company. Therefore, we must not forget to focus on the exploitable and to drop the useless data. This is why a clear objective must be defined at the outset. Therefore, only the data that enables the right actions to be taken should be valued. If you cannot act on a data, analyzing it would be a waste of time.

While choosing the type of data to be collected, you must ask yourself if this data allows you to act or make decisions. If not, you must look for ways to rectify the situation.

7. Accept change

As with any other project, the success of a Big Data project will only be possible if all parties involved accept the change. Big Data implies a major change in the way the company operates and it is necessary to tame this change. The survival of the company depends on it. A company will not be able to compete without making the transition to the digital age.

Already many economic players are engaged in this process of change and are committed to reviewing the way they create value.

8. Proceed in small steps

The improvements implied by Big Data will not appear as if by magic. You have to have the patience to let the transition happen little by little. Undertaking a Big Data project with impatience can ruin its chances of success.

So start with small projects and make sure they will deliver optimal performance without risk. After a series of small projects that work, it will be time to move on to larger projects once your method has been proven. The company will have had time to become familiar with all aspects of data analysis and management.

The progressive growth of projects creates a constant dynamic and generates a climate of trust at all levels of the organization. It will then be time to make the most significant changes that will ensure the future of the company. Trying to proceed without the required experience represents too great a risk. Creating several small projects allows you to develop good expertise without risk.

 

The Big Data will make a big leap forward for companies that will have been able to take advantage of its benefits and change their organizational culture, do not hesitate to call on professionals like Ryax to accompany you.

The Ryax Team.