Data is the corollary of the digital transformation of organizations. Every day, every moment, we all produce a lot of data. An interaction, a hesitation, a like, a sharing, a purchase…All these data are compiled, aggregated and analyzed by data experts.
They are called Data Analysts. Between marketing and IT, between mathematics and management, they are able to make the data speak to make the right decisions and make recommendations and predictions.
An area that is growing more and more, but how far?
The Data Analyst: the digital guide to the data
Like most web-related functions, Data Analyst’s business is relatively new. Their goal is to explore the data at their disposal with statistical, mathematical and computer tools. Some of these tools are developed by specialized publishers and Data Scientists. The analyst does not conceptualize the tools, instead, they use the tools to find answers to complex problems.
The purpose of the Data Analyst’s work is to dissect and explore data in order to render a relevant analysis to customers. It is a dual profession that is both technical and managerial, because the Data Analyst can work for an agency and be in direct contact with external clients; or for a large group, and support internal clients, such as the marketing or sales department.
Data analysis requires a great sense of organization
It also requires good critical thinking and good analytical and modeling skills. But most of all, you have to like the numbers! If Excel is a must, the data analysis also passes and especially by more specific languages and technologies such as Python language or SQL.
Finally, as complex as it may seem, data analysis requires clear and understandable restitution. This is why the Data Analyst should not deliver raw results. They must be a good storyteller to popularize, put in perspective and captivate his audience, a role with very high added value to support the growth of companies.
Data and marketing: an inseparable duo
Data has never been so numerous. Take a simple example: sell a plane ticket at the best price. For businesses, the goal is to fill devices while maximizing profitability, a difficult equation incorporating hundreds of variables that are all interdependent. Setting the price of a single ticket requires the operation of many algorithms and computer programs that work continuously and update the data in real time.
All this information is essential for the company, and especially for marketing. It is indeed with a better knowledge of data and critical variables that it becomes possible to make the right decisions at the right time.
Transforming raw data into actionable decisions is not a straightforward path
While large groups have quickly understood the impact and importance of data, many companies, including SMEs, are still far from it. Data analysis is a springboard and a lever for development. But this can only be done in the case of a well-structured infrastructure and ecosystem.
This is why many Data Analysts work on two aspects: on the one hand, the analysis of complex and highly engaging subjects that requires intense work with data, and on the other, a consulting role to support the transformation of business in the world of data.
Well accompanied, the marketing function takes full advantage of the work done with the data. The goal is no longer Big Data, but smart data: useful data for relevant decisions.
The future of data analysis
There will be more and more data and the evolution of technologies makes this work extremely valuable. Indeed, the data is presented today differently and via new platforms. In this sense, the Internet of Things (IoT) represents the next evolution of data analysis and management.
Between the medical data collected from the connected watches, the displacement data related to autonomous vehicle projects or delivery by drones, those living in connected homes (enclosure, alarm, remote monitoring, household appliances …) or companies (sensors, factory 4.0, digital twins …), the flow is continuous.
Data Analyst’s business will gradually change
They will specialize by sector, according to more and more specific issues, and when you add the subjects of Artificial Intelligence, machine learning or Blockchain, the projects are almost infinite.
Being able to analyze data means having a very valuable anticipation and prediction capacity for companies, an area that continues to develop and for which profiles with a dual manager-engineer with a specialization in digital are very sought after.