Data Engineering

Data engineering is a division of data science that deals with the practical implementations of analysis and data collection. Data scientists use large sets of information in answering questions; this information is collected and validated through certain mechanisms. For this work to have value, it has to be applied to real-world operations through certain mechanisms. These are the two engineering tasks: the application of science to practical and functional systems.

With the pursuit to become AI-driven and with the onslaught of corporate digital transformations, it is clear that companies need Data Engineers to lay the groundwork for successful data science initiatives. They are needed in companies to process the data in a way that enables them to derive value from it. Some top companies that use data engineering are IBM, Salesforce, Alteryx, Cloudera, Segment, Crunchbase, Google, and Oracle

Why opt for Data Engineering with Trugo?

Trugo’s data engineers bring advanced analytics for decision-making to your company. We will be responsible for the design, construction, and constant improvement of your company’s analytics infrastructure. Our data engineers do not complain about problems after discovering them, instead, they are problem solvers who are well equipped with the knowledge of the relevant tools needed in fixing these problems. The appropriate and lead the problems to resolution; they are equipped with knowledge of relevant tools and languages for data management as well as a general knowledge of a range of fields.

Benefits of Data Engineering

1. Problem Solvers:
The best data engineers are restrained, determined, and focused. They can see how and why data pipelines work, and if something goes wrong, they work to produce a solution. Good data engineers love to learn; their interest encourages them to recognize a solution or to think of an alternative solution to a problem. They are familiar with different types of data sets and distinctive programming languages.


2. Find hidden patterns using data:

Data engineers are tasked with discovering patterns in data sets and creating algorithms to help make raw data more valuable to the company. A significant set of technical skills are needed for this job. This includes a vast knowledge of multiple programming languages, SQL, and database design. Data engineers work with various departments to understand company heads’ requirements.

3. Data Acquisition:
​Data Engineers use sampling signals to measure real-world conditions and convert the resulting samples into digital numeric values that can be manipulated by a computer.

4. Building algorithms to give simpler access to data:
​Data engineers are often responsible for building algorithms to help give simpler access to data. For this to be accomplished, the objectives of the company and the client must be thoroughly understood.