DATA ENGINEERING 101:INTRODUCTION TO DATA ENGINNERING.
Tags: codenewbie, dataengineering, beginners, programming
Published: 2022-08-24 14:50:00

When you hear about data engineering what comes in your mind? According to me its basically the act of coming up with systems to facilitate the gathering and making use data. The data collected is used to enable subsequent analysis and data science which mostly work hand in hand with machine learning.

**what do data engineers do** They develop and maintain the architecture used in various data science projects. They are responsible for ensuring that the flow of data between servers and applications is uninterrupted.

**This question comes up, now that i know what data engineering is what do i need to become one?**

**1.**  **coding**- In data engineering coding is like food lol! you cannot do without it. It's an highly valued skill for data engineers. Examples of programming language are: python, Ruby, mat lab and Golang

**2.** **Data warehousing** - we now know that data engineers are responsible for storing and analyzing a huge amount of data. So they need to be familiar with data warehousing solutions like panopy/Redshift, which are crucial in data engineering role.

**3.** **Knowledge of operating systems** - Being an engineer you need to have a better understanding of operating systems like Linux, Windows, macOS and UNIX

**4.** **Database systems** - As an engineer  you need to have a deep understanding of database management. Since **Structures Query language (SQL)** is the most widely used solution, Having a deep understanding of it is crucial.
**5.** **Data analysis** - Most employers expect you  to have a strong understanding of analytics software's to be precise Apache Hadoop-based solutions like MapReduce, Hive and HBase.

**6.**  **Critical thinking skills** - Are you a critical thinker? You need to evaluate issues and develop solutions that are both creative and effective. Why? Most of the time you will be required develop a solution that doesn't exist. Critical thinking is key.

**7.** **Basic understanding of machine learning** - ML is mostly used by data scientists, Basic understanding of ML  will help you in building your knowledge of data modelling and statistical analysis to create solutions that are usable to your peers and by so doing you become outstanding.
**8.** **Communication skills** - Let go of the introverted mentality and network, you need to network in order to learn and share ideas and suggestions with people around you.

Along the way am sure you seen Machine learning, Data scientists and Data analysts and you're wondering who are these people?
well!

**Data scientists** Analyses and interprets complex digital data such as the usage of a website, especially in order to assist a business in its decision making.

**Data analyst** Gathers and interpret data in order to solve a specific problem.

**Another question comes up is data scientist better than data engineer?**

 unfortunately no, Data scientists can interpret data only after receiving in it's appropriate format while a data engineer gets the data to the data scientists so data scientists need to be equipped with the necessary skills to become data engineers. As of 2022 Data engineers are more in demand than data scientists.

**Parting shot**
You  can be anything you want to be. Don't say there is no time just Begin...Take action!
Happy learning!!