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Moving from Big Data to Smart Data in 10 Steps

To make the best use of the new black gold that is data companies must begin by eliminating internal and external obstacles that prevent them from optimizing the potential of customer information.

It is a widely accepted fact that the collection and use of data is an essential step for any organization wanting to be successful, regardless of its market. But the main challenge for businesses is how to extract useful information from this huge amount of data. From our latest study on the subject, here are 10 steps to internally deploy a true data culture and leverage smart data.

To make the best use of this new black gold, companies must start by eliminating internal and external barriers that prevent them from maximizing the potential of customer data. This includes raising employees’ awareness of the need for accurate data and analysis, and providing them with the tools they need to capture, manipulate, clean up and manage accessible information.

Here are ten steps to go from Big Data to smart data and use your data to their full potential.

1. Prepare the data carefully

Essential step but too often seen as superfluous and tedious, the preparation phase must be the cornerstone of your smart data strategy. According to a recent survey, One-third of IT professionals spend between 50% and 90% of their time cleaning raw data and preparing it for integration into a company’s systems, and for 28% of companies the difficulty is to find the right data to exploit. It is for these reasons that it is important to think ahead of what you are looking for precisely and how you are storing your data.

2. Update your software

Companies need to ensure that their systems remain relevant and have the computing power to manage the volume, accuracy and diversity of these systems. It is an investment sometimes heavy, but necessary. Choosing Cloud solutions can also be an alternative, allowing you to reduce your initial investments and pay on demand.

3. Integrate all your information system

Many companies the acquisition of the appropriate analytical tools and techniques is a difficulty. This is why new software must integrate with the current information system. This integration must allow each point of contact with customers across all channels to be accessible to all who need it in the business, thereby improving the customer experience.

4. Give a central place to the data

Companies should give a central place in which an aggregation of data is kept and maintained in an organized way.  A repository may be directly accessible to users or may be a place from which specific databases, files, or documents are obtained for further relocation or distribution in a network. A repository may also be just the aggregation of data itself into some accessible place of storage or it may also imply some ability to selectively extract data. Related terms are data warehouse and data mining.

5. Introduce a true culture of data

For a smart data strategy to be truly effective, it must not only include CIO teams, but also other business lines. The adaptation of the corporate culture is an obstacle preventing companies from optimizing the potential of customer data. This acculturation must enable employees to understand how essential it is to collect customer information and manage it rigorously in order to serve the business.

6. Link your data to enrich and decrypt them

It is essential to clarify and / or establish the connections and relationships between the different entities in a dataset to draw relevant lessons. Given the amount of information generated and the number of departments involved, the challenge is to innovate how to store this information. This can for example be done with graph-oriented databases, where each entity integrates the list of its connections to other data, all being clearly structured and accessible in a few seconds.

7. Visualize the data to make them perform

Having access to useful data is of little interest if you do not understand them. Visual representations of the data (for example, detailed maps for location data) make them easier to interpret, but also make them usable and understandable by other parts of your organization.

8. Empower employees to collaborate

This goes hand in hand with a data culture, it is essential to improve collaboration between different departments to optimize the data and circulate them from one team to another. The company must also provide its employees with specialized tools for data management and customized training to ensure that each management is able to use its data.

9. Secure the data

For many companies, the consent of consumers to share their personal data and the rules prohibiting the collection of certain information constitute obstacles. This is especially true as new regulations like the GDPR (General Data Protection Regulation) has come into force and establish corporate responsibility for data protection (or neglect of data protection).

10. Refresh data in real time

According to Global Data Quality Research, Every 30 minutes, 120 business addresses and 75 telephone numbers change, 20 CEOs leave and 30 new businesses are created. For data to be valuable, it must be updated to keep pace with changing customer needs. Indeed, finding the right data to use to carry out this follow-up is a difficulty for 28% of the companies surveyed.

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