Is It Worth It to Learn Tableau for Data Science in 2024?
At EdgeRed, we’re continually on the lookout for innovative tools that sharpen our capabilities in the expansive field of data science. As 2024 unfolds, we’re eager to share our insights into why Tableau is
not just holding its ground but also continues to be a must-have skill for any data science professional.
Despite being established nearly two decades ago, Tableau has impressively managed to stay at the forefront of data visualisation tools. Its sustained relevance can be attributed to constant updates, a strong community driving innovations, and a commitment to user-centric enhancements. Adaptable and versatile, Tableau is more than just a tool; it’s a powerhouse enabling data scientists to tackle contemporary challenges and stay a step ahead in the dynamic world of data analytics.
Top reasons why Tableau is still relevant today:
- Industry standard: Tableau remains an industry standard, widely utilised across sectors for data visualisation and analytics.
- Ease of use: Its user-friendly interface allows for quick creation of visually appealing and interactive dashboards.
- Powerful features: Tableau offers a wide range of powerful features, catering to diverse data visualisation and data analysis needs.
- Integration capabilities: Tableau has native integration with a large number of data sources, facilitating comprehensive data analysis.
- Commmunity support: With a large user community, Tableau provides ample support, resources, and collaborative opportunities.
- Continuous updates: Regular updates and enhancements ensure that Tableau users have access to the latest tools and enhancements, keeping them at the forefront of data visualisation trends.
Why Do We Use Tableau Instead of Excel?
In our practice at EdgeRed, while we acknowledge the simplicity and usefulness of Excel and Google Sheets for spreadsheet-oriented tasks, when it comes to data visualisation, Tableau is a very capable tool and a first choice for many of our clients. Its superior handling of large datasets, along with the ability to craft interactive and insightful dashboards, are features that Excel cannot parallel.
Tableau’s strength lies in its capacity to perform complex, on-the-spot calculations and seamless integrations with a wide array of data sources, which positions it as the preferred choice for sophisticated data analysis and visual storytelling. Additionally, Tableau works very well with Excel and Google Sheets, as the seamless interoperability between the two platforms streamlines data preparation and analysis processes, resulting in more comprehensive insights and actionable outcomes.
Why Is Tableau Necessary for Data Analysis?
Tableau transcends the bounds of traditional reporting by converting raw data into engaging, interactive narratives. This form of storytelling is not merely about presenting data; it’s about enabling business leaders and decision-makers to derive meaningful insights swiftly. Best practices for data visualisation should be followed to make the most of Tableau.
Tableau fosters an environment where numbers become stories that lead to informed decision-making. It empowers users to delve into the nitty-gritty of their data without losing sight of the bigger picture.
How Can Data Engineers Become Tableau Experts?
For those looking for a different path in their data career, data engineers are uniquely positioned to leverage their expertise in data manipulation and apply it to the visual domain, making Tableau an indispensable tool in their arsenal. To excel with Tableau, data engineers should consider the development of their commercial acumen, recognising the growing demand for professionals who can not only analyse data but also effectively communicate insights to stakeholders.
Tableau offers a wealth of learning resources tailored to meet the evolving needs of data professionals in 2024. Its comprehensive training programs, active community forums, and the opportunity to work on real-world projects provide data engineers with the tools and support needed to become Tableau virtuosos.
What Are Some Complementary Tools to Use with Tableau?
At EdgeRed, our approach to data analysis is holistic; we recognise that Tableau is part of a broader ecosystem of tools that, when used together, provide an end-to-end analytical solution. Alteryx, with its prowess in data preparation, Python’s capabilities in advanced analytics, and Google BigQuery’s efficiency in managing big data operations, all integrate seamlessly with Tableau.
This synergistic toolset keeps up with the modern data stack. It enables us to tackle any aspect of data handling and analysis, ensuring we deliver comprehensive solutions to our clients.
EdgeRed’s Adventures with Tableau
In our own journey, Tableau has been a trusted companion:
- We’ve seen a major food procurement company’s reporting transform from a jigsaw of spreadsheets into a cohesive set of Tableau dashboards, providing real-time insights on inflation across product categories.
- Our work for a radiology network involved migrating their data models and business logic into SQL, Alteryx, and Tableau, showcasing our ability to handle complex data systems and bring them into the clear visuals of Tableau dashboards.
- For a marketing consultancy, our deployment of Google Apps Script applications was complemented by the powerful visualisations of Tableau, allowing for a seamless storytelling of data insights.
These projects are a testament to how Tableau keeps us at the forefront of data science. It’s not just about playing with data; it’s about making the data play for us. For each of the projects, we bring industry best practices to enhance clarity, consistency, and effectiveness in presenting data.
About EdgeRed
EdgeRed is an Australian boutique consultancy specialising in data and analytics. We draw value and insights through data science and artificial intelligence to help companies make faster and smarter decisions.
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