Data and its linked fields have experienced several changes throughout the years. Previously, the focus was on translating information into relevant analyses in order to aid in decision making. Today, in this increasingly digital world, data jobs have gained traction and are becoming more prominent by the day.
What is Big Data?
The term Big Data was first used in 2005 by Roger Mougalas. It is defined as a large amount of data that is impossible to manage and process using traditional tools. For example, in the marketing sector, some specialized companies extract a large volume of data which they transform and store. Data Analysts and Data Scientists analyze this stored data to transform it into usable data, guiding decision making in a very precise and accurate way. Today, many organizations are data-driven, and their activity is focused on the information and guidelines of Data Scientists.
What is a data engineer?
Data engineers are in charge of identifying patterns in data sets, by creating and implementing the right algorithms in order to make sense of that data so as to aid in market understanding or decision making. Because of this, a data engineer must have a diverse range of technical abilities, such as a deep understanding of SQL database design and different coding languages. Beyond their technical abilities, data engineers must also be able to communicate with the different departments of an enterprise in order to fully comprehend their needs and be able to deliver the adequate information required.
What is the role of a data engineer?
Data engineers can have different roles depending on the type and size of the organization that they serve. A data engineer at a small company does not have the same roles and objectives as a data engineer at a large organization focused on Data Lakes or Data Warehouses. However, there are some shared tasks that almost all data engineers need to accomplish:
- Data architecture: a data engineer must be able to work on data architecture in order to provide adequate data when it’s needed and translate that data into relevant insights. They must also work on continuously making sure that the architecture is aligned with the goals of the organization.
- Research: data engineers should be able to make their skillset useful in research. This goes from data collection to the creation of datasets, to data optimization and analysis.
- Task automation: data engineers work on continuously improving business processes by making them more efficient through automation.
- Closely monitoring new technology trends.
- Development of jobs or data pipelines.
What’s next for Big Data?
For a long time, Big Data has been seen as an infinite pool of intel that guides decision-making. This large, ever-growing amount of information has been a synonym of possibility, advantage, and opportunity. However, information overload is an issue that has recently become very prominent. In 2022, new trends are becoming more and more prominent in the field of Big Data, such as Fast Data and Smart Data. Smart Data refers to data that has a meaning. This is a data form in which algorithms have been inserted in order to extract relevant trends, patterns and statistics. In other words, Smart Data is Big Data with an added layer of intelligence. Fast Data refers to information streaming in real time, enabling instantaneous decision-making. This type of data generates insights that are actionable at the same moment in which they are happening. It allows for quicker decision-making and increases the efficiency of the actions taken by solving problems before they proliferate.
Why is real-time data analysis useful? It allows decision makers to solve problems more quickly, from detecting faulty products in a manufacturing line to sales forecasting to traffic monitoring, among many others. These next years are very promising for the field of data, especially for fast and smart data. Data Engineers are on the verge of a golden age in which they will become a necessity for businesses of all sizes, sectors and activities.