Over the past decade, there has been a significant increase in the volumes of data generated. It is estimated that nearly 2.5 quintillion bytes of data are generated daily. As a result of the explosion in data, the Data Analytics Industry has been transformed. This transformation has led to the birth of Business Intelligence Engineers. Business Intelligence Engineers work collaboratively with Business Data Engineers and Business Intelligence Analysts. You will get to know more about these professionals in the further sections.
Business Intelligence is something that every company and organization strives for these days. Business Intelligence is trending in today’s world, and so are the careers associated with it. It enables businesses to transform raw data into intelligent and actionable insights that aid in strategic decision-making. There are many BI (Business Intelligence) tools available these days that ease the work of Business Intelligence Engineers.
This article will give you a comprehensive guide to Business Intelligence Engineers. You will also explore various roles and responsibilities associated with Business Intelligence Engineers. It will also give you an idea about the Tech Stack used by them. Let’s get started.
Table of Contents
What is Business Intelligence?
Business Intelligence (BI) refers to the strategies and technologies used by businesses to analyze data and manage business information. Reporting, Online Analytical Processing, Analytics, Dashboard Development, Data Mining, Process Mining, Complex Event Processing, Business Performance Management, Benchmarking, Text Mining, Predictive Analytics, and Prescriptive Analytics are all common functions of business intelligence technologies.
BI tools can handle large amounts of structured and sometimes unstructured data to assist in the identification, development, and creation of new strategic business opportunities. They want to make it simple to interpret large amounts of data. Identifying new opportunities and implementing an effective strategy based on insights can give businesses a competitive market advantage and long-term stability, as well as assist them in making strategic decisions.
Enterprises can use Business Intelligence to support a wide range of business decisions, from operational to strategic. Product positioning and pricing are examples of fundamental operational decisions. At the most general level, strategic business decisions involve priorities, goals, and directions.
BI is most effective in all cases when it combines data derived from the market in which a company operates (external data) with data derived from company sources internal to the business, such as financial and operations data (internal data).
Key Features of Business Intelligence
Here are some notable features of BI:
- Self-Service Reporting: Due to the complexity of traditional business intelligence, only a small number of employees within an organization have the technical expertise required to create and maintain reports.
- Fast Implementation: One of the major drawbacks of traditional business intelligence software is that it frequently necessitates a complex, time-consuming implementation process. This process is made even more difficult for businesses that lack the in-house capabilities to carry it out themselves.
- Analyses in Memory: In terms of powerful yet simple functionality, in-memory analysis can be one of the most important business intelligence features. The in-memory analysis enables line of business users to analyze data without the need for special skills or the assistance of IT specialists.
- Data Visualisation: Data Visualization has been a key component in the overall effort to make Business Intelligence more mainstream and widely available. In recent years, it has become one of the most important business intelligence features.
- Advanced Security: Without a doubt, one of the most discussed Business Intelligence features, particularly when it comes to Cloud BI solutions, is security. Concerns about security have previously led to businesses preferring on-premise business intelligence solutions; however, these concerns are starting to fade as vendors offer more robust and stringent security measures.
- OLAP: In addition, OLAP data is organized hierarchically and stored in cubes rather than tables. OLAP’s functionality makes it one of the must-have business intelligence features to look for in a vendor.
Who are the Business Intelligence Engineers?
Business Intelligence Engineers are the professionals who are responsible for creating the Reports, Statistical Models, and Visualizations that the company needs to make strategic decisions. Business Intelligence Engineers collaborate with Business Data Engineers and Analysts to convert raw data into meaningful and actionable insights that can help create KPIs (Key Performance Indicators). They are also in charge of improving and streamlining the BI (Business Intelligence) tools and strategically implementing them.
Business Intelligence Engineers also contribute to business growth by making informed Business Decisions, assisting in Financial Planning, and improving the Customer Experience. It’s an excellent career for professionals who wish to demonstrate their business expertise. Hence, a career in this sector can be both satisfying and lucrative.
What is the Skill Set Required for Business Intelligence Engineers?
Every field requires a specific set of skills. A few of the key skills that must be acquired by Business Intelligence Engineers include:
1) Data Analysis
Business Intelligence Engineers are mostly concerned with leveraging data to make better judgments. They must be proficient at analyzing a variety of Data Sources and drawing reliable conclusions from them. Moreover, expertise in Data Analysis is a must for Data Modelling and Warehouse Designs.
2) Knowledge of BI Tools
Business Intelligence Engineers require prior expertise in designing and configuring the customer BI (Business Intelligence) products. They should have in-depth knowledge about various BI tools and their underlying infrastructure. They should also know scripting languages like Python and have experience with Data Visualization frameworks for creating custom BI products.
3) Problem Solving
Business Intelligence Engineers are also responsible for developing business strategies and utilizing data to solve real-world challenges. They should be able to visualize the data properly so that relevant KPIs can be created. So, they need to be good at Problem-Solving as well.
4) Communication Skills
Business Intelligence Engineers require extensive collaboration with Business Data Engineers, Business Analysts, Developers, etc., and should be able to successfully convey their findings. Sometimes, they are also responsible to communicate the findings to clients who are not technically sound. Thus, they require excellent Communication Skills.
5) Debugging Skills
Strong Debugging skills are required at every stage of Design, Development, and Maintenance. Moreover, every business data is associated with a certain level of complexities like security issues, permissions, updates, etc. Thus, Business Intelligence Engineers should have strong Debugging Skills to rectify technical problems.
6) Business Acumen
Business Intelligence Engineers should have in-depth knowledge of the Business Model so that the business gains maximum value from the KPIs (Key Performance Indicators). They also play a critical role in strategic decision-making that can help in the growth of the business. Thus, Business Acumen is one of the key skills that must be acquired by Business Intelligence Engineers.
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What are the Key Responsibilities of Business Intelligence Engineers?
The responsibilities associated with Business Intelligence Engineers are very vast. Given below are the key responsibilities associated with Business Intelligence Engineers:
- Business Intelligence Engineers are responsible for providing a clean, accurate, and trustworthy dataset that can be utilized to develop and monitor KPIs (Key Performance Indicators) in a scalable manner.
- Business Intelligence Engineers must collaborate with Business Data Engineers, Data Analysts, etc. to transform the data into valuable information that can be utilized to make better strategic decisions and provide better customer service.
- Business Intelligence Engineers are responsible for creating technical documents that can guide the end-users on how to use the product. For example, API documentation, known technical issues documentation, etc.
- Business Intelligence Engineers and Business Data Engineers should collaborate to build and schedule ETL or ELT pipelines in production. In some circumstances, it may be necessary to work with Software Developers as well to create Data Streaming Solutions.
- Business Intelligence Engineers are responsible for making strategic decisions related to developed software and also monitor the entire deployment process. During the pre and post-launch stages, they are also responsible for testing and troubleshooting.
Earnings of Business Intelligence Engineers
The earnings of a Business Intelligence Engineer depend on a varied range of factors. It depends on where you are working, how much experience you have, what skills you have, and what educational qualifications you have. Working for a top organization might increase your chances of earning more than candidates with equal abilities and expertise. These salaries are being discussed to give you an idea of how the industry works and what you may expect when you start working as a Business Intelligence Engineer.
The typical base salary for a Business Intelligence Engineer is Rs. 5,10,000/- per year. However, the earnings can be increased up to Rs. 12,87,000/- per annum based on the experience. The lower limit is Rs. 2,00,000/- per annum. Moreover, you can improve your chances of earning more than the average salary by controlling the elements that are under your control. For example, you can choose to work somewhere that pays more than the national average or you can also apply to organizations that pay better than the competition.
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Tech Stack for Business Intelligence Engineers
Every profession requires a different set of Tech Stack based on the requirements. A Tech Stack is termed as the set of technologies that a professional or an organization uses to build and run a project or an application. A Tech Stack typically consists of Frameworks, Programming Languages, BI Tools, Data Warehouses, Databases, etc. Choosing the right Tech Stack for any professional is very crucial.
The set of technologies used by Business Data Engineers can be different from Business Intelligence Engineers. The Tech Stack utilized by Business Intelligence Engineers include:
1) Cloud Data Warehouse
The core of Business Intelligence is the Data Warehouse. A Data Warehouse is a central location where you can replicate data from multiple sources and analyze it to make strategic decisions. Some of the popular Data Warehouses include Amazon Redshift, Google BigQuery, Microsoft Azure, Snowflake, etc.
2) Programming Languages
Business Intelligence Engineers should be familiar with Programming Languages and should have a strong foundation of Data Structures and Algorithms. The Programming Languages that are most popular among Business Intelligence Engineers include Python, Pyspark, Scala, etc.
3) Data Streaming Tools
Business Intelligence Engineers should have adequate experience with Data Streaming Tools. Data Streaming is the next big thing in Analytics and Machine Learning because it allows businesses to make quick decisions using real-time information. One of the popular Data Streaming tools used by Business Intelligence Engineers is Apache Kafka.
4) Data Ingestion Tools
Business Intelligence Engineers should have good knowledge of Data Ingestion Tools and their workings. Data Ingestion is the process of replicating the data from a source to a destination. Some of the popular tools that can be utilized by Business Intelligence Engineers include Hevo Data, Stitch, Fivetran, etc.
5) Data Manipulation Tools
Business Intelligence Engineers should be familiar with the tools that can help them to modify the existing data and convert it into an organized and easy-to-read format. Some of the popular Data Manipulation Tools that can be utilized include SQL (Structured Query Language), Apache Spark, LookML, etc.
6) Data Visualization Tools
Data Visualization is one of the key aspects of any Business Intelligence profile. Business Intelligence Engineers should have a good understanding of Data Visualization Tools. Some of the popular Data Visualization Tools include Tableau, Looker, Mode Analytics, etc.
7) ETL Pipelines Scheduling
Business Intelligence Engineers should collaborate with Business Data Engineers for the ETL (Extract, Transform, and Load) Pipelines Scheduling. One of the popular tools for ETL Pipeline Scheduling is Apache Airflow. Apache Airflow enables you to construct workflows using the Python programming language, which can then be easily scheduled and monitored.
These are the major Tech Stacks that are associated with Business Intelligence Engineers.
This article gave insights into the Business Intelligence Engineers and how they collaborate with Business Data Engineers, Analysts, Developers, etc. to solve real-world problems. You have also got to know about the Key Skills, Responsibilities, Earnings, and Tech Stack associated with Business Intelligence Engineers. Thus, Business Intelligence Engineers play a very crucial role in any organization.
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