Azure Data Analyst (Microsoft Certification)

Creative and Analytical Thinking

Curiosity and Creativity are the key qualities one should possess to become a Certified Data Analyst. Having a solid foundation in statistical methodology is important but looking at problems with a creative and analytical lens is equally important to unravel different layers of a problem.

Data Visualization (Power BI)

Data Visualization is one of the most important skills one should possess to become a Certified Data Analyst. A Data Analyst must master the art of representing the data in an easy-to-understand manner. A good Data Analyst knows what types of Visualization Charts to use, how to scale visualizations, depending on the type of audience.

Power BI is a business analytics solution that lets you visualize your data and share insights across your organization or embed them in your app or website. Connect to hundreds of data sources and bring your data to life with live dashboards and reports.

Data Warehousing

Sometimes you need to work in tandem with the Data Engineering team in the backend as a Data Analyst to connect databases from multiple sources, create a Data Warehouse, and use Queries to extract and manipulate the data. Hence, to become a Certified Data Analyst, you must be familiar with the key concepts associated with Data Warehousing.

Data Cleaning

Data extracted from a database is not always clean and ready for analysis and this is where Data Cleaning comes into the picture. To become a Certified Data Analyst, you must be able to remove corrupt records from a dataset which can hamper your analysis.

Mathematics and Statistics:

Objective decision-making is a crucial part of problem-solving. To make decisions objectively, you need to rely on Mathematics and Statistics. You need to find patterns, segment them, and make predictions based on historical information. Therefore, you must have a strong foundation of Mathematics and Statistics to come up with the optimized solution to a problem and efficiently perform Data Analysis.

SQL Server Integration Services (SSIS)

This is a useful and powerful Business Intelligence Tool. It is best suited to work with SQL Server Database. It is added to SQL Server Database when you install SQL Server Data Tools (SSDT)which adds the Business Intelligence Templates to Visual studio that is used to create Integration projects.

Database Query Languages (Azure SQL, ETL)

The most common Query Language used by Data Analysts is SQL and there are many variations of this language including PSQL, PL / SQL (Procedural Language / SQL). You must be proficient in Query languages to become a Certified Data Analyst.

Azure SQL Database
Support modern cloud applications on an intelligent, managed database service, that includes serverless compute.

Azure SQL Managed Instance
Modernize your existing SQL Server applications at scale with an intelligent fully managed instance as a service, with almost 100% feature parity with the SQL Server database engine. Best for most migrations to the cloud.

SQL Server on Azure VMs
Lift-and-shift your SQL Server workloads with ease and maintain 100% SQL Server compatibility and operating system-level access.

Extract, transform, and load (ETL)
it is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store.

Microsoft Excel

Microsoft Excel is a Spreadsheet program offered by Microsoft which is extensively used for performing Data Analysis. As a Data Analyst, you should be able to work with Microsoft Excel and understand advanced modeling techniques.

Programming Languages

Data Analysts need to be fluent in one language and have some hands-on experience with it. Data Analysts use Programming Languages such as R and Python for Data Collection, Data Cleansing, Statistical Analysis, and Data Visualization.

Machine Learning

Machine Learning is not a mandatory skill to become a Data Analyst but knowledge of Machine Learning is an added advantage when it comes to performing exploratory analysis.

Strong and Effective Communication Skills

Once a Data Analyst is able to uncover hidden insights from a large data set, then the findings need to be communicated to the stakeholders who are involved, and this is where Soft skills play a major role. As a Data Analyst, you should be able to communicate effectively and pitch your findings to the prospect teams.