Digital Transformation... It's on everyone's mind more and more every day, but without proper data usage, significant advances in companies will be hard to achieve.
Without proper data handling, achieving digital transformation will be very complicated. The problem with many companies is that they are not yet aware of the importance of having valid data that truly adds value to their businesses. Nowadays, they tend to store data but not analyze it. They continue to rely on people's past experience to obtain good results, but we need to be aware that the models are changing, and these traditional methods won't be as effective unless we incorporate data-driven knowledge.
The sustainability of companies in the coming years will be directly related to the proper use of information (data). That's why new concepts related to the necessary roles for leveraging this information are emerging.
By way of comparison, we can use the example of when companies used to ask the resident IT person to solve all problems related to the concept of "computing" that could arise within the company... Over time, we realized that the concept of "computing" was much broader, and depending on how technology evolved and the needs of the companies, we saw that this "IT person" started specializing in different areas based on the required needs... They couldn't know everything... at least, they couldn't devote time to everything.
In the IT sector, we are more or less familiar with the new concepts that have emerged with the new technologies used within IT departments: Analysts, Developers, Programmers, experts in Cybersecurity, etc., etc., with diverse knowledge in Cloud systems, Electromechanics, Security, etc., etc., and with specific knowledge of the tools each of them uses. In other words, we have made significant progress in terms of profiles in this regard.
Nowadays, we generate more data through technology and from the users themselves. Companies have improved their IT systems and are capable of collecting a high level of information (data)... But..
How many individuals/companies really know the new data-related profiles to make their businesses evolve and become more profitable through all the information they are generating?
Do they understand the differences between these profiles? Do they know how to use, segment, clean, and leverage all that information for real and profitable benefits within a short time frame that allows them to make quick decisions?
I dare say that we are still far from fully understanding and appreciating the importance of valid data... I venture to assert that for now, we are only collecting information... In many cases, we have information without knowing where it comes from, or without even intending to generate it... We have information because our systems store it, or because legislation requires it... or because other departments deem it interesting... or it gets generated on social media...
In many cases, information is requested just for the sake of it, to fill gaps, to appease others, to create more work, to store just in case, etc.
"In general, there are no plans to handle all that data, no plans to generate new information based on the data we already have... no plans to listen to what social media is saying.."
....Turning data into value is not easy, and it requires the right tools and knowledge. It needs to be worked on from the ground up with the support of new technical and business profiles that bring teams together to gain better visibility into all available information (structured, semi-structured, and unstructured).
I'm sharing these concepts as a quick overview to help us all gain a better understanding of these new profiles, which are undoubtedly essential and will continue to be in demand within companies in the coming years if they want to improve their results and optimize their resources.
Data Scientist - They work closely with decision-makers in companies. They can gather large amounts of complex data, especially unstructured data, and transform it into more usable formats that provide value to the company. They are capable of solving statistical problems, seeking patterns and trends among the data. They have a broad business understanding and communication skills to convey results to the rest of the organization. They work extensively on machine learning to predict the future based on past data and use multiple sources of information not only related to the business itself. They clean and remove any invalid information. With all this information, they pose new questions that can add value to the company. They seek knowledge through data.
Data Analyst - Collaborates in data analysis by collecting information related to the business and working with Data Scientists. They are also involved in data extraction, processing, and aggregation for analysis and report generation. They primarily use programming tools like R, Python, etc., to address specific business problems. They search for and obtain insights from available sources to reveal metrics that enhance the company's efficiency. They sift through data to address specific business problems.
Chief Data Officer - This role can be defined as the person responsible for all data within the company, both from a technological and business perspective, as well as security. Data is a vital asset for companies and needs to be managed effectively.. The Chief Data Officer's mission is to oversee data at all times, ensure its security and quality, and create a data strategy at the enterprise level. Data governance is one of their main responsibilities, as is driving innovation, digital transformation, cost reduction, and revenue generation. They provide the company with insights and support on topics such as products, customers, operations, and markets. In short, they are responsible for using the asset that is data to create business value through it.
Data Engineer - Typically specializes in databases, data processing systems, and programming. They are heavily focused on designing, developing, and maintaining systems within a Big Data project. In essence, they manage available data and create the infrastructure to generate the processes needed for data treatment. They work closely with Data Scientists.
Data Manager - Oversees and implements various data systems within a company. They organize, store, and analyze data efficiently. They design databases and ensure data security by establishing policies and rules for data management, as well as data quality. Their decisions add value to the company at a high level.
Data Steward - This is a professional in Data Management whose primary responsibilities include identifying, defining, and establishing the value of data for their company. They are responsible for monitoring data quality, reliability, and its selection for business intelligence. They oversee the data lifecycle and implement policies for daily operational and administrative data management. Their work primarily focuses on the business side of the company.
Data Custodian - Another professional in Data Management who performs tasks similar to a Data Steward but from a more technical IT perspective, related to databases, integrations, etc. Both Data Steward and Data Custodian are new areas within Data Management that directly report to the Chief Data Officer.
Citizen Data Scientist is a professional who is referred to as a data scientist but creates or generates models that leverage predictive or prescriptive analysis while their primary responsibility or work falls outside the field of statistics and analysis. Their mission is to accelerate the organization's transition to artificial intelligence and machine learning in an easier and more cost-effective way. Collaboration with Data Scientists is crucial for them. They are professionals whose main activity is unrelated to technical analytics, but they can carry out such analytics at a proficient level. They have tools that automate and simplify tasks that, until recently, only Data Scientists and Data Engineers could perform.
Data Artist - Within Big Data, the data artist is the graphic designer. They have expertise in graphic design and information technology. They understand processes and are capable of presenting data in a more visual format. Their mission is to create visual effects and graphics with data. For example, they can generate interactive dashboards that display real-time information in a simple and understandable manner. Through this "Technical" visualization, the goal is to bridge the gap between business stakeholders and data scientists by improving data information and communication.
As we can see, there are different roles, but in many cases, they overlap due to the needs and resources of each company, or even a lack of clarity about the necessary profile. As mentioned at the beginning, these are new concepts that will gradually define their responsibilities more clearly and provide increasing value to companies, much like "computer professionals" have done over time.
Companies like Amazon, Netflix, Apple, Facebook, Microsoft, Spotify, McDonald's, Coca-Cola, and many others understand the importance of data analysis for their businesses. We all know their results. It's time to start considering whether your company needs to hire data-related profiles to improve profitability and sustainability or at the very least begin to recognize the importance of data management and analysis.
