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Top 10 Tools Data Analysts Should Learn in 2023

According to the World Economic Forum, Data Analyst is the most sought-after role for employers. Every company deals with a huge amount of data used to make important business decisions. Be it data analytics or data science, the demand for data-related roles has increased significantly.
To fulfil your responsibilities as a data analyst, there are many tools you need to be familiar with. Some you may be more common, however if you’re looking to solidify or get more knowledge on what it takes to be a data analyst in 2023, these are some of the most popular tools right now to get everything you need from data scraping to visualisation.

Data Analysis – What exactly does it mean?
Essentially, it’s the process of cleansing, converting, and modelling data to find relevant information for business decision-making. The process offers helpful insights and statistics, frequently presented in charts, graphics, tables, and graphs, which lessen the risks associated with decision-making.

Role of a Data Analyst
Data analysts look for solutions to customer-related issues by analysing large data sets. They have the expertise and abilities to transform unprocessed data into knowledge and insight specifically for informed business choices. As more and more businesses collect data at all stages of work Analysts are not limited to one specific task.

Top 10 Tools for Data Analysts
Data processing and manipulation, relationship and correlation analysis between data sets, pattern and trend identification, and interpretation are all made simpler for users by data analysis tools. Briefly discussed below are the Top 10 Tools Useful for Data Analysts:

1. Google Sheets
Probably one of the most obvious on the list that most will be familiar with, Google Sheets is a spreadsheet tool available through the Google Drive service. Aside from simply populating data in spreadsheets, there are some built-in rapid analysis tools in Google Sheets that can provide you with a quick overview of your data and some insightful information. Data transformation and analysis are made simple with Google Sheets thanks to its built-in functions and visualisation features. For data analysts, Google sheets also has some add-ons for Google analytics. The add-on gives you the ability to visualise more data without needing to code.

Benefits of Google Sheets:
  • Free
  • Cloud-based
  • Automatically saves files
  • Many people can work on one file at the same time
  • Add-ons and for Google Analytics and other Google integrations

Data Analysis Tools For Data Sourcing

2. Zapier
Zapier is an online tool that connects your favourite apps and services to others, automating operations. You can automate tasks as a result without having to develop an integration or API yourself or by a professional. This automation tool's goal is to assist you in developing a workflow that is more intelligent and personalised. This would also remove the need for cleaning, copying and pasting data from one app to another, an essential time saver when working with large amounts of data. It could also be used to trigger notifications, emails and other forms of communication.

Benefits of Zapier:
  • User-friendly
  • Time-saving
  • Replaces manual admin
  • Helps you scale your business
  • Automatically triggers communications i.e for leads

3. Tableau
The industry-leading business intelligence tool Tableau is used to analyse and understandably present data. Working with a live data set and spending more time on data analysis rather than data wrangling are both made possible by Tableau. The foundation of this tool is "VizQL," the primary query language of Tableau. The products offered by Tableau include Tableau Server, Tableau Public (free), Tableau Reader, Tableau Online, and Tableau Desktop.

Benefits of Tableau:
  • Intelligent dashboard
  • User-friendly
  • Unrestricted data explorations
  • Automatic updates
  • Prompt analytics process and outcomes

4. HubSpot
HubSpot is a marketing, sales, and service platform that aids businesses in finding clients, turning leads into sales, and closing deals. These types of systems are typically called CRM or customer relationship management software and there are others on the market today. You can integrate your marketing, sales, and customer care efforts, add automation, obtain more insight into your prospects, and more. Individuals in the team such as sales managers and marketers may use the software for daily operations, the Data Analyst may manage systems within Hubspot to effectively build lists for leads, or collate data in dashboards for further analysis.

Benefits of HubSpot:
  • Free to use
  • Social Management Features
  • Website Integration
  • Communication Tracking
  • Combine data from multiple sources
  • Track and understand your full customer journey through data. 

Data Extraction Tools


5. SQL
SQL for data analysis refers to the database querying language's use of relational databases as well as its capacity to interface with several databases simultaneously. Since it combines a surprisingly easy learning curve with a complicated depth that enables users to construct powerful tools and dashboards for data analytics, SQL is one of the most widely used and adaptable languages.

Benefits of SQL:
  • Easy to learn and understand
  • User-friendly language
  • Helps in retrieving big data from multiple databases
  • Provides standard documentation to users

6. Google Analytics
Google Analytics is a web analytics service that offers data and fundamental analytical capabilities for marketing and search engine optimization (SEO) needs. It is employed to monitor website performance and compile visitor data. Organisations can use it to identify the main user traffic sources, evaluate the effectiveness of their marketing initiatives and campaigns, measure goal completions, identify patterns and trends in user involvement, and gather additional visitor data such as demographics. Page tags are used by Google Analytics to collect user information from each website visitor.

Benefits of Google Analytics:
  • Tracks online traffic
  • Understands user behavior
  • Data reports and customization
  • Improve SEO and content

7. Fivetran
After a quick setup of five minutes, Fivetran duplicates programs, databases, events, and files into a high-performance data warehouse. Fivetran is a powerful extract, load, and transform (ELT) tool. It focuses primarily on the extraction and loading component of the ELT paradigm and provides users with a library of connectors that can be used to connect sources to targets with essentially no coding or technical knowledge. This means you havea a centralised place for data and are able to cross reference and take action more quickly. 

Benefits of Fivetran:
  • Quick to set up
  • Offers multiple Connectors
  • Makes ELTs easy to maintain
  • Less number of developers
  • Decreases required time for managing data

Data Visualisation Tools


8. Power BI
Microsoft Power BI is frequently used by data analysts to build interactive representations using its business intelligence features and capabilities. With Power BI, users can independently create and share dashboards and reports. It also supports various data sources. This is used for visualising data and important when reporting information to other teams and making final business decisions related to your results.

Benefits of Power BI:
  • Ease of data analysis
  • Effective data connectivity
  • Data Protection across various Office platforms
  • Easy integration

9. Google Data Studio
Google Data Studio is another visualisation tool for designing attractive, adaptable, interactive, and responsive reports and dashboards. To make the reports easy for everyone to generate and comprehend, it is possible to design panels using templates, utilise the widest range of graphs, maps, and tables, apply your brand identity, and use additional resources.

Benefits of Google Data Studio:
  • Free to use
  • Interactive live reports and filtering
  • Easy report sharing
  • Data blending

Python for Data Analysis

10. Python
Python is a well-known multi-purpose programming language that is extensively used for its adaptability and a large library of useful libraries that are useful for analytics and complicated calculations. Due to Python's versatility, thousands of libraries, including the widely-used Pandas, are devoted to analytics. Python's ability to swiftly generate and maintain data structures is one of its most popular applications; for example, Pandas provides a wide range of tools to manipulate, analyse, and even visualise complicated datasets and data structures.

Benefits of Python:
  • Easy to learn
  • Flexible
  • Open-source
  • Well-supported

The tools listed above aren’t the only ones available for analysts, however they should give a well rounded tool kit for most day-to-day tasks, from basic coding skills, exporting data, storing data, visualising data and developing a business case based on results. If you’re keen to learn more, all of these tools are taught at the Le Wagon Data Analytics Bootcamp. If you’re still not sure, we also run a variety of free workshops to get an introduction and see if it’s the right career move for you.

Learn Data Analytics at Le Wagon


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