In the age of big data, businesses are constantly seeking ways to extract valuable insights from their data in order to drive informed decisions. This has led to an increase in demand for data analysts globally. If you are contemplating a career in data analytics, this article is just for you! This article will explore the essential skills, tools and techniques, including SQL and Tableau, that will empower you to kick start your career in this exciting industry.
Building a Strong Foundation
What is Data Analytics?
Before you embark on your career as a data analyst, it is essential to gain a clear understanding of what it entails and its pertinence across industries. Previously, we gave a brief introduction to data analytics and what it encompasses. To sum it up, there are four different types of data analytics: i) descriptive, ii) diagnostic, iii) predictive, and iv) prescriptive. To learn more about the various types of data analytics, refer to our previous article.
Essential Skills to Excel as a Data Analyst
Next, explore the key skills that will help you thrive as a data analyst. These skills include, but are not limited to, being proficient in a variety of programming languages (e.g., SQL, Python), having a strong base in statistics and mathematics, critical thinking and effective communication.
SQL: Data Manipulation and Extraction
Introduction to SQL
Structured Query Language (SQL) is an indispensable and popular programming language intended for managing and interacting with relational databases. As the cornerstone of data manipulation and extraction, SQL can be utilised for a variety of functions, ranging from querying and filtering data to updating and organising it in a structured manner. As a start, familiarise yourself with the basics. That is, SQL syntax, basic queries, and the SELECT statement to retrieve, filter and aggregate data.
Advanced SQL Techniques
Once you are comfortable with the fundamentals, you can then advance to sophisticated SQL concepts like joins, subqueries, and indexing to analyse complex datasets. Explore how to leverage SQL functions and conditional statements to execute calculations and draw meaningful conclusions from your data.
Optimising SQL Queries
To get the most out of SQL, pick up the essentials for writing efficient and optimised SQL queries. From indexing strategies to query optimisation techniques, having a good grasp of these recommended practices will considerably improve the productivity of your data retrieval and manipulation.
Tableau: Data Visualisation
Introduction to Tableau
Tableau is a popular data visualisation tool that allows users to convert raw data into comprehensible and compelling visualisations. Designed with accessibility in mind, Tableau allows users (regardless of tech prowess) to easily create insightful charts, graphs, dashboards, and maps to present findings in a visually appealing manner via its interactive interface. Here is how the tableau interface looks like:
Creating Engaging Visualisations
To create clear and impactful visuals, first understand the principles of data visualisation. For instance, learn how to choose the appropriate chart type, use colours effectively, and highlight key findings in your visualisations.
Interactive Dashboards and Storytelling
Further dive into Tableau’s dashboard and storytelling capabilities. For example, combine multiple visualisations into interactive dashboards that allow users to explore data from multiple angles. Effectively convey the intended message to your audience via compelling visual representations of data.
To learn how you can leverage SQL and Tableau in your path to launching a successful career as a Data Analyst, check out DA100: Data Analytics with SQL and Tableau by Heicoders Academy. Here is a sample project created by a learner who has taken DA100:
Tips for Achieving Success in Data Analytics
Aside from the above, below are some additional tips and tricks for achieving success in Data Analytics.
Ensuring Data Quality. First, ensure that the data you are working with is reliable and consistent by cleaning and validating your data before analysing it. This will maintain data integrity and increase accuracy of results.
Build Domain Knowledge. Take a deep dive into the industry or domain you are working in. Awareness of the specific business context will also enhance the applicability and impact of your data analysis.
Constant Learning and Upskilling. In an evolving industry like data analytics, be sure to be in-the-know of new advancements by remaining committed to continuous learning. Stay updated with the latest tools, techniques and trends through online forums, courses, etc. For instance, get certified with Heicoder Academy’s newly launched Data Analytics Nanodegree, which will equip you with the skills vital to kick starting your new career as a data analyst.
Embarking on a career in data analytics is an exhilarating and fulfilling journey, and tools like SQL and Tableau will be your trusty companions in this adventure. Get ready to shape the future with your newly acquired expertise and begin on a fulfilling career as a data analyst!