Data Analysis: 3 Tools Every Beginner Must Have

Data Analysis: 3 Tools Every Beginner Must Have

‍

• Advantages of starting a career in Data Analysis
• 3 tools every beginner should add to their portfolio

‍

If you’ve read our post on how to get started in Data Analysis, you may be wondering which tools are important for you to possess now. 

While there are various tools for data analysis, as a beginner, you should use the basic ones first. This is simply because they are common and you can easily navigate them. 

But before we delve into it, let’s highlight some reasons you should consider starting a career in data analysis 

‍

Why Should You Learn Data Analysis? 

‍

• It fosters trust:

Whether you’re a business owner, an  employee, or a business analyst,  data analysis helps people trust you better. Customers, your bosses, your colleagues. 

As an employee, when you base your recommendations and decisions on data analysis, it demonstrates your commitment to thorough research and evidence-based insights. Colleagues and superiors will trust your expertise and rely on your recommendations, knowing that your conclusions are grounded in data rather than mere intuition. 

For business owners, data analysis offers valuable insights into customer preferences, behavior, and needs. By conducting analyses, you can gain a deeper understanding of your target audience and tailor your products, services, and marketing strategies accordingly. When customers perceive that you've made data-driven decisions, they are more likely to trust your brand, perceiving you as a knowledgeable and customer-centric business owner.

‍

• It helps you make informed decisions:

By leveraging data analysis, you can gain valuable predictive insights that help anticipate future occurrences and trends. This then empowers you to make proactive decisions, enabling you to prevent potential losses, identify opportunities, optimize outcomes and mitigate risks.

According to Forbes, “With quality data on your side, you will have greater confidence when making business decisions, while also becoming more agile.”

So what then are the tools you need as a beginner?

‍

3 MUST-HAVE TOOLS FOR EVERY BEGINNER

‍

1. EXCEL

Excel is versatile and offers a range of functionalities for data analysis. It allows you to organize, manipulate, and analyze data using formulas, functions, and other built-in features. 

Here are some tasks you can perform with Excel. 

• Data Cleaning:

Excel provides a variety of features to help you clean data for analysis. For instance, you can use the "Remove Duplicates" feature to eliminate duplicate entries in a dataset, ensuring data integrity. Excel's filtering and sorting capabilities allow you to easily identify and remove outliers or errors in your data. 

‍

‍

And Excel's conditional formatting feature can help highlight inconsistencies or patterns in your data, making it easier to identify and correct any issues.

You can also use functions like AVERAGE, MEDIAN, and STANDARD DEVIATION to calculate descriptive statistics for a dataset. 

‍

‍

‍

‍

• Data Manipulation:

With functions like CONCATENATE, LEFT, RIGHT, and MID, you can combine or split data across different columns. Excel's IF function allows you to perform conditional calculations based on specific criteria. 

‍

‍

These data manipulation features are particularly useful when dealing with large datasets or when performing data transformations for further analysis.

‍

2. Power BI: 

Power BI is a powerful data visualization and business intelligence tool developed by Microsoft. 

It allows you to connect to various data sources, create interactive visualizations, and share reports and dashboards. 

Power BI enables you to explore and present data in a visually compelling manner, making it easier to communicate insights and findings to stakeholders. It also provides beginner-friendly drag-and-drop features and does not require extensive programming knowledge.

Let's dive deeper into its features and benefits:

‍

• Data Connectivity:

Power BI enables you to connect to a wide range of data sources, including databases, cloud services, spreadsheets, and online platforms. You can import data from sources like Excel, SQL Server, SharePoint, Salesforce, Google Analytics, and many more. This versatility allows you to consolidate data from multiple sources into a single platform for analysis.

‍

• Interactive Visualizations:

With Power BI, you can create highly interactive and visually appealing dashboards and reports. It offers a rich set of visualization options such as bar charts, line graphs, maps, scatter plots, and more. You can customize the appearance, colors, and formatting of visuals to effectively convey insights and patterns in your data. Power BI's interactive features allow users to explore data by drilling down, filtering, and slicing it based on different dimensions.

‍

‍

• Data Exploration and Analysis:

Power BI provides a range of tools for data exploration and analysis. You can create calculated columns and measures using DAX (Data Analysis Expressions) language to perform advanced calculations and create new derived fields. Power BI also offers a variety of data transformation options, such as merging tables, creating relationships, and applying filters, enabling you to shape and manipulate your data for analysis.

‍

3. Google Sheets

Quite similar to Excel, Google sheets provides many of the same functionalities as Excel, allowing you to perform data analysis tasks in a web-based environment. Google Sheets is particularly useful when working with distributed teams or when you need to share and collaborate on data analysis projects.

‍

‍

So, multiple users can simultaneously work on the same spreadsheet, making it ideal for team projects. You can all view changes made by others in real-time, leave comments, and suggest edits, fostering seamless collaboration on data analysis tasks. 

Its built-in QUERY function allows you to perform more advanced data manipulations and aggregations. And you can also use functions like IF, VLOOKUP, and FILTER to conditionally extract and organize data.

‍

‍

Bottom Line

To start a career in Data Analysis, you need to equip yourself with the right tools. But to learn how to use these tools effectively, you need to enrol in a course. 

‍

‍

‍