Become a Business Intelligence Analyst With These 5 Skills

Become a Business Intelligence Analyst With These 5 Skills

Business intelligence is the most essential yet underrated profession in business. It helps companies make knowledgeable decisions by analyzing data, which will help organizations become more efficient and achieve their targeted goals. Recent studies show that in 2024, the job market for business intelligence analysts is expected to grow by 14%, faster than the average of all other occupations. If a person loves analyzing data and finding smart solutions to use that data to improve business growth, then a profession such as business intelligence analytics is the best for them.

In this article, we will discuss the most essential technical skills for business intelligence analysts and their average salary.

Top 5 Technical Skills for Business Intelligence Analysts

1. Data architecture and design 

The data architecture and design for business intelligence analysts is the way of organizing and structuring the data to identify valuable information that helps in decision-making for the organization. The main aspects of data architecture are:

  • Data Sourcing and Integration: Business intelligence analysts need access to various data sources like databases, data warehouses, APIs, and spreadsheets. After that, they identify the relevant data sources and integrate all data into a single data space.   
  • Data Modeling includes structuring and creating the data report needed for the analysis. Data design includes defining entities, their attributes, and links between the data elements. BI analysts usually work with dimensional modeling for data warehouses for faster queries and report executions.
  • Data storage: this means choosing the best place to store data. It automatically incorporates classical relational databases, NoSQL databases, data lakes, or their combinations according to the type and scale of the data.
  • Data transformation and ETL: ETL stands for extract, transform, and load processes, essential for cleaning, transforming, and preparing data for analysis. Business Intelligence analysts work with ETL tools to check data quality and consistency.
  • Metadata Management: metadata is the summary of basic information about the data that makes tracking and working with data relatively easier. Metadata management means handling the metadata to construct an outlining model, parenthood hierarchy, and the history of each specific data. Business Intelligence analysts need to document metadata to confirm data governance and collaboration on the task.

2. Data visualisation

Data visualization means gathering information, data represented in graphical form, such as a pie chart or other visual representation. Data Visualisation is important for Business Intelligence analytics. With the help of data visualization, a BI analyst can analyze data and make smart decisions for the organization’s growth. Data visualization allows people to understand patterns and relationships and spot emerging trends in the data easily and quickly that can go unnoticed in the tables or spreadsheets. 

Data visualization tools like Tableau, Infogram Sisence, etc, connect with data sources such as relational databases. This data will be stored in the cloud and retrieved for analysis. Business Intelligence analysts can select the best way to present data from numerous options. The BI analysts should ensure that the data represented is accurate and up-to-date. The visualization should be consistent in reports and dashboards to avoid confusion and misinterpretation.

3.SQL: Structured Query Language

SQL is one of the most essential technical skills for business intelligence analysts. It stands for structured query language, a programming language that helps create, monitor, and access relational databases. SQL has a simple syntax that makes it easy to understand and learn; most BI analysts enjoy working in SQL because of its power, speed, and flexibility. Business Intelligence Analysts commonly use SQL for data analysis functions like reporting and decision-making. Some of the commonly used SQL in BI analysis are:

  • Data Retrieval: BI Analysts use SQL queries to extract data from data sources. They write SQL queries to get the required datasets from relational databases like MySQL, PostgreSQL, SQL Server, and Oracle.
  • Data Manipulation: Because of SQL, analysts can manipulate and rearrange data as they desire. They can filter, sort, aggregate, and transform data into tables using SQL functions, where, group by, join, with, and different sorts of syntax.
  • Data Analysis: BI analysts use SQL to achieve different types of analysis, such as longitudinal or cohort analysis, segmentation, or performance analysis. They type in SQL queries, construct KPIs (Key Performance Indicators), and discover patterns in huge amounts of data.
  • Report Generation: SQL is used for report building and dashboard development. BI analysts first write SQL queries to extract data for reports and then format the results in a way suitable for visualization tools or reporting platforms.
  • Data Integration: BI Analysts write SQL code to have data from different apps in one place. They use SQL queries to filter and export specific datasets (e.g., data blending, data transformation, and data migration) from one software tool to another.

4. Cloud computing 

In business intelligence analysis, cloud computing means using cloud-based services and platforms to process and analyze huge sets of data so that you can obtain important information. Cloud computing allows BI analysts to access data warehouses, analytics tools, and computing power at low investments. This approach brings several benefits, such as scalability, flexibility, and cost efficiency, since organizations can use resources according to the market’s demand and only have to pay when they use it. Also, cloud computing helps BI analysts by giving them data and analytics dashboards from any location with an internet connection. Finally, cloud-based BI analysis helps organizations to make fast and effective data-driven decisions that promote innovation and competitive advantage in this business world.

5. Statistical analysis 

In business intelligence, statistical analysis is a very important component. This mathematical method analyzes data and finds trends, patterns, and insights that can help any business make strategic decisions. Overall, it is a numerical way to understand what is happening in the business and predict what might happen. BI analyst deals with large datasets and empirical and sectorial data in their job roles. They also apply regression analysis, hypothesis testing, and data mining to reveal patterns, draw conclusions, and make organizational decisions. BI analytics utilization allows companies to know well what they are doing providing a basis for more smart decisions made with the help of data-based insights. 

What Is The Average Salary of a Business Analyst?

The average salary of a business analyst in India depends on many factors, including experience, Industry, expertise, education, location, and company size. For example, the average business analyst’s salary for freshers is USD 70,660 per annum, while for an experienced professional, it is around USD 83,008. Similarly, the average salary in Mumbai is 6,59,688 INR per annum, while in Bangalore, business analysts earn around 7,97,044 INR per annum. That’s why the earning potential of a business intelligence analyst is the combination of these factors, aligning with their skills and market demands. In the end, the salary of business intelligence analysts in India ranges from INR 400,000 to INR 1,500,000 per annum, which makes the average salary of INR 700,000 per annum.


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