Big Data Engineering in Collaboration with IBM

Big Data Engineering is an information technology profession in which the individual is in charge of developing, creating, testing and for the maintenance of complicated data processing systems that work with large amounts of datasets.

A big data engineer is responsible for integrating, cleaning, transforming and enriching various different forms of data such that downstream consumers can comprehensively extract statistical information. Big data basically means large volumes of data whether structured or unstructured which is difficult to manage.

Humans create a lot of data and organizations collect this data from various resources. Sources of data could be smart Internet of Things or IoT devices, social media, audio, video, images, etc. This data is utilized to predict trends, prevent diseases, advertising, combat crime and such.

Anybody can become a big data engineer if they desire to do so. A career in big data engineering is pretty rewarding. First and foremost thing is that you need to have a bachelor’s degree in computer science or information technology or any other related field. This ensures that you have a foundation in the basic concepts although you can even have a non programming background as well.

Then you need to develop your data engineering skills like coding, relational and non relational databases, ETL systems, data storage, automation and scripting, machine learning, big data tools, cloud computing and data security.

Being well versed in coding is vital to this profile, various programming languages suitable for big data engineers are SQL, Python, Java, Scala and R. Extract, transform and load systems is the procedure through which a data engineer can move data from databases to data warehouses. Writing scripts to automate repetitive tasks is also needed.

There are tons of courses available online and offline in the name of big data engineering but most of them are of no worth in the industry. Organizations search for a skilled candidate, who is certified from a reputed institute. DataTrained presents you the best online course for Big Data Engineering which is in collaboration with IBM or International Business Machines.

DataTrained is India’s number 1 Ed Tech startup and IBM is a world renowned organization. Together we joined forces to bring you the best in class content. Our tutors and industry experts teach you everything from a very basic to advanced level.

We provide weekend live classes keeping in mind that working individuals would also be joining in our course. In this way they don’t have to leave their current jobs and fresher graduates can also get benefitted from this arrangement. Here are the salient features of our big data engineering course:-

• Access to IBM’s Big Data Tools
• IBM BigInsights products
• 100+ hours of learning
• Practice Test Included
• Certificate of completion from DataTrained and IBM

According to a web portal glassdoor the average salary of a big data engineer in India is ₹ 8 Lakhs per year. This is based on 399 salaries listed and last updated on 6 Jan 2022. The salary ranges from ₹ 4 Lakhs per year to ₹ 17 Lakhs per year. The average salary on L2 seniority level is ₹ 8 Lakhs per year, on L3 level is ₹ 15 Lakhs per year and on L4 seniority level is ₹ 21 Lakhs per year.

Top companies in India for big data engineering are :-

• Tata Consultancy Services : TCS provides an average package of ₹ 6,03,997 per year, which is based on 40 salaries.
• Cognizant Technology Solutions : This company provides an average package of ₹ 8,67,429 per year, which is based on 27 salaries.
• Infosys : Infosys provides an average package of ₹ 6,00,000 per year, which is based on 17 salaries.
• Exadatum : This company provides an average package of ₹ 7,19,088 per year, this is based on 17 salaries.
• Knowledge Lens : This company provides an average package of ₹ 6,67,106 per year, this is based on 16 salaries.

On another web portal ambitionbox, the average salary for a big data engineer is stated to be ₹ 8.5 Lakhs per year. The salary ranges between ₹ 2.9 lakhs per year to ₹ 22.3 lakhs per year. These figures are based on 6.6k salaries and last updated on 12 Jan 2022.

Payscale web portal states the average salary for a big data engineer to be ₹ 8,57,157 per year. With salary ranging between ₹ 3.89 lakhs per year to ₹ 20 lakhs per year. This is based on 1,532 salary profiles and last updated on 21 Dec 2021.

Data engineers are required to work with specialized tools to handle data. Every system has different sets of challenges. An increase in the raw amount of data has created a demand for big data engineers in various industries. Let us have a look at various tools that data engineers utilize :-

• Amazon Redshift : This is a cloud warehouse managed by Amazon. It is one of the most widely used tools among data engineers. It is very easy to use and facilitates hundreds of businesses.
• SQL : Structured Query Language is used by data engineers to perform ETL tasks. It is especially utilized when data source and data destination are the same database type.
• Python : One of the most popular programming languages ever Python is an easy to learn and general purpose language. It is utilized for coding ETL frameworks, automations, API interaction and many more.
• Tableau :Its main functionality is to accumulate and extract data stored at different locations. It is then used to create dashboards.
• Apache Spark : It is open sourced and utilized for extensive data processing. It supports many programming languages such as Java, Scala, Python and R.
• Looker : It is utilized for data visualization purposes and has a LookML layer. This layer is for depicting dimensions, calculations and relationship with data in SQL databases.
• Snowflake : It is a cloud based data warehouse platform. It supports 3rd party tools, data cloning, etc.

Big data engineering is a little challenging but with right guidance and support anybody can excel in this field. DataTrained provides one on one assistance in our Big Data Engineering course. We have designed our course in such a way that even a non programming background student can understand.

We provide you support at every stage of your learning with us. If you have any questions and doubts you can raise a ticket and get it resolved within a short period of time.

To be a successful big data engineer the candidate must have technical and non technical skills. First and foremost is to have a bachelor’s degree in computer science or information technology or any other relevant field.

In terms of technical skills they must be knowledgeable in various programming languages like Python, Scala, R, C++, etc. The candidate must be aware of SQL databases, NoSQL databases, Apache Spark, Apache Airflow, ELK Stack, Hadoop Ecosystem, Apache Kafka, Amazon Redshift.

Non Technical skills include analytical skills, data visualization, problem solving ability, data mining skills, familiarity with public cloud and hybrid clouds. Hands- on experience is a plus point.

According to a report by IT Chronicles, Companies generate around 2,000,000,000,000,000,000 bytes of data per day. By 2023 this data would be worth around USD 77 Billion. So it is quite evident that a large amount of data is getting produced. As a result demand for big data engineers is going to rise exponentially for the near future as companies have realized the importance of data mining.

At DataTrained we have transformed thousands of careers. Upon enrolling in our big data engineering course our mentors will assist you at every step. We will provide you with all the skills and hands-on experience on projects. Upon completion of course we will prepare you for various interview questions. Our team includes experts of their field and industry professionals. So wait no more and join today!

A beginner in the big data engineering field must have first hand experience with working on different big data projects for deep understanding of the concepts. We have formed a list for top big data projects that a student can do, here is the list:-

• Sentiment analysis with Apache Spark
• Log Analysis with Spark streaming and Kafka
• Google reviews data analysis using Azure Databricks
• Realtime data analysis of ola cabs with Databricks
• Covid 19 Data analysis