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Updated: Feb 5, 2023

While ‘#data-driven culture’ makes some Companies understand and use the true power of data, ‘data strategy’ remains one of the most popular topics in management reviews. What does it really involve ?

A data strategy is a roadmap describing how a business will collect, store, analyse and use data to achieve its goals. It is customised for every business specificities : customers, products, data sources, … and aims at creating efficiencies through organisation.

Data strategy is about making sure that data will be available tomorrow to create a point of difference and connect with customer, there are 6 essential steps towards implementation :

1. Make sure #data-strategy represents #business strategy

Data has become one of the most important aspects of any business. In today's economy, data is used to make strategic decisions, track progress, & optimize performance. As a result, it is essential that data strategy represents business strategy. The first step is to anticipate data needs. What information will be needed to make informed decisions? What processes to collect this data? Whatever route , the important thing is that data strategy helps achieve business goals.

2. Understand #organisational structure

Data strategy should anticipate organisational responsibilities, departmental demands and technological capabilities when it comes to managing data. It should identify who is responsible and accountable for managing data. Data strategy should always remain aligned with the organisation's strategy.

3. Combine all data in one place

Data is a double-edged sword. Too much data can be overwhelming, and poorly managed data can lead to inaccurate conclusions. As a result, clear and concise data strategy is essential. One of the most important aspects of data strategy is data consolidation in a central location.

4. Build an architecture that can stand the test of time

The data architecture should anticipate the needs of the organisation and easily #adapt to changes. Additionally, it should be able to stand the test of time, remaining effective even as technology changes. Correct design from the start is essential.

5. Data strategy should be designed for the future of #AI

Data is the lifeblood of machine learning. As machine learning and AI continue to evolve, it is crucial that data strategy is designed to anticipate the needs of these ever-changing technologies in order to keep up with the pace of innovation.

6. Data strategy should be designed for optimum #data-protection

As customers increasingly entrust businesses with their personal information, it is essential that data strategy is designed with optimum protection in mind. By being proactive and prepared, businesses can go a long way towards protecting their customers' data.

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