Data engineering is a science that helps to make data beneficial and usable for its consumers. In other words, data engineering helps create raw data analyses to provide predicting data models to exhibit short and long-term trends. A recent Gartner report indicates that in the year 2020, over 80% of the companies will be working on the Cloud platforms, and of this, over 40% would go for public cloud platforms. A recent webinar depicted how more than 60% of the businesses in Canada were forced to expedite their technology plans like Cloud migration primarily due to the global pandemic. In the year 2021, and “Data Lake” is rapidly evolving as a rapid shift from on-premises servers to the Cloud at a startling speed.
Big Data skills are significant in data engineering-related job roles. This stands true from everything related to designing, creating, building, and maintenance of data pipelines to collecting raw data from varied sources, and then consequently optimizing data for performance. Data engineering professionals perform plenty of tasks to seek an understanding and knowledge of big data frameworks, databases, infrastructures, data containers, and a lot more.
Here, let us discuss five very important tech skills that one must have to succeed in their data engineering career journey -
- Data warehousing - A data warehouse is a system that helps companies in organizing, and analyzing big data in a meaningful manner. Data Warehouses are central repositories of streamlined and integrated data from diversified sources. These data sources can be ERP Software, CRM solutions,s or accounting software. Businesses utilize this data to create reports, perform data analysis and data mining to achieve useful insights.
- AI and Machine learning - A knowledge of the AI terminology has today become a significant skill in a data engineer job role. Incorporating machine learning into big data can certainly advance the process by discovering the data engineering trends and patterns. M/L algorithms can be used to identify the incoming data and patterns and transform them into insights. An awareness of machine learning needs a solid foundation in mathematics and stats, and programming languages like Python, and Cloud-based tools like AWS Sage maker.
- Data Pipelines - Data transformation, which is done to ensure the efficient development of the “Data Lake” data for analyzing and visualizing it in the future, is another significant skill set required for data engineering. Additionally, processing real-time streams, data warehouse queries, JSON, CSV, and raw data is a daily affair. Knowledge of tools like Apache Kafka, Amazon Web Services (AWS), Cloud Development Kit (CDK) is also a must-have skill for a data engineer.
- Programming Language - JAVA, Python, and Scala are some very popular languages for data engineers. Python helps with statistical analysis and modeling. And, Java is used to work with data architecture frameworks. These languages are preferred by programmers the most as it helps them write maintainable, reusable, and complex functions. These languages are efficient, versatile, suitable for text analytics, and provide a strong foundation for data engineering services and big data support.
- Database Tools - Data storage, organization, and management are crucial for data engineering job roles. The two kinds of commonly used databases are SQL-based and NoSQL-based. SQL-based databases are MySQL and PL/SQL that are used to store structured data. Whereas, NoSQL-based databases such as MongoDB, Cassandra, and others can be used to store big volumes of structured, unstructured, and semi-structured data as per the requirements of the application.
In this article, we looked at the skills and tools that are required in the data engineering market today. Now, let us take a look at how VirtueTech can take care of your data engineering needs.
Data engineering services facilitate existing data science solutions and add value to the business by saving costs and time. With the right set of skills and tools, data engineers can essentially become more rewarding. VirtueTech makes data engineers more efficient and data consumers more confident. This is how VirtueTech helps companies get more value from their data.
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