Tableau-Desktop-Specialist reality - Tableau Desktop Specialist Updated: 2024

Tableau is a popular business intelligence and data analytics tool renowned for transforming complex data into actionable insights. Used by a diverse range of industries, from healthcare to finance, Tableau empowers organizations to make data-driven decisions. Its intuitive interface and powerful visualization capabilities enable users to create compelling data stories, making it a preferred choice for professionals seeking to leverage data effectively.

Whether you are a seasoned data analyst or a business leader looking to harness the power of data, Tableau offers a suite of tools to meet a variety of analytical needs.

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What is Tableau used for?

Tableau is widely used for reporting, data analysis and decision-making processes across departments in an organization. Its applications range from tracking key performance indicators to conducting in-depth market research and forecasting future trends.

As a flexible data visualization and business intelligence tool, Tableau allows users to connect to a variety of data sources — from simple spreadsheets to complex databases — and transform this data into interactive, visual dashboards and reports. With these visualizations, users can identify trends, patterns and insights that might not be obvious in raw data.

How do you use Tableau?

Using Tableau begins with connecting to your data source. Tableau is compatible with numerous data formats and sources, including Excel, cloud-based data and SQL databases. Once connected, you can use its drag-and-drop interface to create visualizations. You can choose from a variety of chart types, apply filters and use drill-down features to explore data in-depth.

SEE: Here’s how to concatenate strings and numbers in Tableau.

Tableau also allows users to create dashboards that combine multiple visualizations, which provides a comprehensive view of the data. Sharing insights is straightforward with Tableau’s options to publish dashboards on Tableau Server or Tableau Online, enabling collaborative decision-making.

Is it easy to learn Tableau?

The ease of learning Tableau largely depends on one’s background and experience with data analysis tools. For users who are familiar with data concepts and visualization principles, it’s relatively straightforward to start creating basic visualizations. However, mastering its more advanced features, like complex calculations and data modeling, may require additional time and practice.

Tableau offers a wealth of learning resources, including online tutorials, forums and training sessions, which can significantly ease the learning process. The active Tableau community also provides a supportive environment for beginners to learn and share knowledge.

Do I need to learn Excel or SQL before Tableau?

While prior knowledge of Excel or SQL is not a prerequisite for using Tableau, being familiar with these tools can enhance a user’s Tableau experience. Excel skills help users understand data organization and basic analysis, which are fundamental in Tableau. As for SQL, its knowledge is advantageous when working with large databases or performing complex data queries within Tableau.

SEE: Discover how to create or use a Top N filter in Tableau.

Still, Tableau is designed to be accessible to non-technical users, including those without a background in these programs, by providing various ways to manipulate and analyze data without needing advanced skills in Excel or SQL.

Key features of Tableau

While Tableau’s most prominent feature is its data visualization capabilities, its intuitive design and data processing and analytics capabilities make it a top choice for teams with varying levels of data experience. Some of these features include:

• Data visualization: Users can create a wide array of interactive and visually appealing charts, graphs and maps to transform complex datasets into understandable and actionable insights, making it easier to identify trends and outliers.
• Drag-and-drop interface: Tableau’s intuitive drag-and-drop interface makes it accessible for users with varying levels of technical expertise to create complex visualizations.
• Advanced analytics: Advanced analytics features, including predictive modeling and trend analysis, help users forecast future trends and make data-driven decisions, even without a deep background in data science.
• Data blending: Tableau’s ability to merge data from multiple sources into a single dataset for analysis is particularly useful when dealing with related data that is stored in different systems.
• Real-time data processing: Tableau’s real-time data processing capabilities allow users to analyze data as it’s being updated, which is ideal for teams that need up-to-the-minute data analysis for timely decision-making.

What is Tableau good for?

Tableau excels in transforming raw data into meaningful visualizations, making it an excellent tool for data-driven decision-making. It’s particularly effective for businesses that need to analyze and interpret large datasets to unearth trends and patterns.

In addition, Tableau is great for creating comprehensive reports and dashboards, which paint a holistic picture of business performance. And Tableau’s real-time data processing capabilities mean that it’s great for scenarios like monitoring live financial markets or tracking operational metrics in real time that need immediate data analysis.

What is Tableau not good for?

For all its capabilities, Tableau has certain limitations. For one, it’s not primarily designed for detailed statistical analysis or advanced predictive modeling, which requires specialized statistical software. Tableau might need to be supplemented with other tools to achieve deep data manipulation.

Additionally, while Tableau can handle large datasets, extremely high volumes of data might require additional data preparation tools to optimize performance. And while its pricing is more affordable compared to competitors, Tableau may not be the most cost-effective solution for very small businesses or individual users who have limited data analysis needs, as its full suite of features might be underutilized in such scenarios.

Top Tableau integrations

Tableau’s wide variety of integrations can be categorized according to cloud services, customer relationship management systems, big data tools, business applications, spreadsheet tools and dashboard application integrations. Focusing on the dashboard applications, some of the integrations you can expect to find on Tableau dashboards include:

• WriteBackExtreme allows users to add data directly within Tableau dashboards, with features for collaboration, data helper, data correction and an administration console.
• Write-Back Form Builder provides the functionality to create forms within Tableau for data entry. It allows users to input and update data directly from the dashboard, making it easier to manage and update datasets without leaving the Tableau environment.
• Pixel Perfect by USEReady is an extension for creating print-ready, well-formatted reports directly from Tableau dashboards, enhancing the precision and aesthetics of printed Tableau visualizations.
• Synchronized Refresh by phData synchronizes dashboard refreshes for all users, enabling real-time collaboration on the same data. It’s particularly useful for teams working simultaneously on time-sensitive data.
• Kinetica Geospatial Analytics by Kinetica allows users to analyze billions of data points on a map, leveraging Kinetica’s database server-side rendering. It’s great for handling large-scale geospatial datasets.

Tableau’s place in the BI and analytics software market

Tableau has established itself as a significant player in the business intelligence and analytics software market. With a market share of 15.09% in the business intelligence category, Tableau ranks highly among hundreds of competitors in this sector.

The acquisition of Tableau by Salesforce in 2019 for $15.7 billion marked a pivotal moment, further solidifying Tableau’s position in the market. This merger into the Salesforce ecosystem has enhanced Tableau’s capabilities, making it an even more powerful tool in the BI and analytics landscape. Tableau’s reputation as a top BI and analytics tool is well-earned, evidenced by its consistent ranking as a leader in Gartner’s Magic Quadrant industry analysis every year since 2012.

Tableau’s main competitors

• Google Looker is a BI and analytics platform that uses its unique modeling language, LookML, to enable highly flexible and powerful data modeling.
• Alteryx offers a data analytics platform that is both code-free and code-friendly with automated workflows and spatial and predictive analytics capabilities.
• Domo provides cloud-based data integration and real-time dashboard creation capabilities alongside a user-friendly interface that enables the easy building of data visualizations and interactive dashboards.
• Databox is known for its customizable dashboards, real-time data tracking and KPI visualization as well as collaboration tools, alerts and notifications that are especially useful for marketing and sales analytics.

Looker and Tableau are both robust business intelligence tools. But which should you choose for your organization? Each solution will import data from multiple sources, provide in-depth BI analysis and produce rich data visualizations. However, Looker can provide more and ease-of-use functionality, whereas Tableau digs a little deeper into large and complex data sets.

The two products are highly rated BI software, frequently praised for their security, technical support and agility. Let’s compare Looker and Tableau to determine which would be best for your organization.

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What is Looker?

Looker is a popular, easy-to-use BI analytics dashboard. Employees can create and share views to dig deeper into the performance of their organization. Looker is owned by Google and is offered at a monthly flat rate per company.

What is Tableau?

Tableau is a data visualization suite primarily used for business intelligence and analytics. Through Tableau, organizations can customize and optimize how they interact with their data. Tableau is currently owned by Salesforce and is offered as a monthly per-user subscription.

Looker vs. Tableau: Comparison table

Looker and Tableau pricing

Starting at $5,000 per month, Looker can be substantially more costly for smaller companies. As such, Looker is ideal for larger companies that want to remain scalable. By comparison, Tableau’s Creator solution starts at $70 per user, making it ideal for smaller businesses.

Looker pricing

Looker pricing is determined by two main factors: the platform pricing cost to run a Looker instance and the user pricing cost for licensing individual users to access the Looker platform.

Looker offers three platform editions:

• Standard: Pay-as-you-go priced monthly at $5,000, or priced annually for a custom quote price.
• Enterprise: Custom quotes.
• Embed platform: Custom quotes.

User license pricing is consistent across each edition.

• Viewer User: $30 per user per month.
• Standard User: $60 per user per month.
• Developer User: $125 per user per month.

Tableau pricing

Tableau’s Creator edition enables users to govern their solution, interact with the software, collaborate through the system and author works based on their datasets. In addition, Tableau offers its Explorer and Virtual editions with limited capabilities.

• Tableau Creator: $70 per user per month, billed annually.
• Tableau Explorer: $42 per user per month, billed annually.
• Tableau Viewer: $15 per user per month, billed annually.

Figure A

Feature comparison: Looker vs. Tableau

Looker vs. Tableau: Main features

Tableau imports structured and unstructured data to build elegant, human-readable visualizations. Looker likewise provides creatable dashboards with rich visualizations for imported data, which users then customize to suit their needs.

Figure B

Both are full-featured BI tools that include these features:

• Mobile support.
• Interactive visuals.
• Analytics dashboards.
• Governance and metadata management.
• Integrated APIs and tools.

Tableau provides advanced data analysis and visualization, but Looker leaves its options exposed and accessible.

Looker vs. Tableau: Performance

Modern companies are crunching increasingly large data sets. How do Looker and Tableau perform when given big data? In most circumstances, they will work with relatively equal effectiveness. Tableau is more effective with extensive data sets, while Looker is more effective than Tableau in a cloud-native environment.

Figure C

Looker vs. Tableau: Analytics

Looker provides prebuilt, configurable code blocks. LookML, a proprietary SQL-like language, can be used to further interact with and analyze data. Tableau’s analytics solutions don’t have this additional abstraction layer, making it more complicated to use but ultimately more configurable.

Looker vs. Tableau: Support

Looker and Tableau both have reliable service and support solutions. Looker leans heavily on online help centers and in-app chats. Tableau provides support through traditional venues, such as a weekday phone line and 24/7 emergency phone support. Both Looker and Tableau have active and vibrant communities and documentation.

Looker pros and cons

Pros of Looker

• With Looker’s unified semantic layer, data professionals can simplify complex data for end users by encoding business logic and metrics within centralized data models.
• Looker’s data model ensures a consistent and regulated real-time view of data across multiple clouds, benefiting the entire organization.
• Organizations can enhance their business decisions by embedding proactive insights directly into their business applications using Looker.
• By automating tasks like data preparation and reporting, Looker streamlines data analysis, leading to time and resource savings and more precise results.
• Looker guarantees enterprise-level security through features like role-based access control, data encryption and audit logging. This ensures data security and compliance with security policies.

Figure D

Cons of Looker

• Businesses that rely on a large number of data sources may encounter limitations with the software as it can only connect to a restricted set of data sources.
• Looker’s analytics are not as deep or configurable in comparison to Tableau’s.

Tableau pros and cons

Pros of Tableau

• Users can expedite the discovery of insights with the assistance of AI-powered analytics.
• Machine learning, statistics, natural language processing and intelligent data preparation are readily accessible.
• Einstein Discovery enables users to make smarter decisions by providing predictions and recommendations within workflows. It enables the creation of predictive models without the need for algorithmic coding.

Cons of Tableau

• Users may experience delays when processing large amounts of data within the system.
• Non-technical users may find it challenging to figure out how to use Tableau’s software as it has a significant learning curve.

Review methodology

This is a technical review using compiled literature researched from relevant databases. The information provided within this article is gathered from vendor websites or based on an aggregate of user feedback to ensure a high-quality review.

Should your organization use Looker or Tableau?

Neither solution is necessarily better, but Tableau is more complex than Looker. Looker provides extensive user-friendly features, such as Looker Blocks, which make it easier to manage analytics views. However, Tableau offers more opportunities for advanced data analytics and management.

A few critical factors will go into deciding whether you want to use Looker or Tableau as your organization’s go-to BI software.

• Ease of use: Are your users deep into analytics (Tableau), or will they need an accessible, easy-to-use system (Looker)?
• Cost: Is your company looking for an affordable solution for a handful of employees (Tableau) or a product that can support a large enterprise at a flat rate (Looker)?
• Capabilities: Do you need to dig deeply into your data (Tableau), or are you more concerned about visualizing and using your data (Looker)?

If your organization wants a fast, easy-to-use system with beautiful data visualizations, Looker is the best option. If your organization is looking for deep data analytics or a cost-effective plan for a small number of people, Tableau is the better BI software.

Your mind is very powerful. Yet, if you're like most people, you probably spend very little time reflecting on the way you think. After all, who thinks about thinking?

But, the way you think about yourself turns into your reality.

The Link Between Thoughts, Feelings And Behavior

Your thoughts are a catalyst for self-perpetuating cycles. What you think directly influences how you feel and how you behave. So if you think you’re a failure, you’ll feel like a failure. Then, you’ll act like a failure, which reinforces your belief that you must be a failure.

I see this happen all the time in my therapy office. Someone will come in saying, “I’m just not good enough to advance in my career.” That assumption leads her to feel discouraged and causes her to put in less effort. That lack of effort prevents her from getting a promotion.

Or, someone will say, “I’m really socially awkward.” So when that individual goes to a social gathering, he stays to in the corner by himself. When no one speaks to him, it reinforces his belief that he must be socially awkward.

Your Beliefs Get Reinforced

Once you draw a conclusion about yourself, you’re likely to do two things; look for evidence that reinforces your belief and discount anything that runs contrary to your belief.

Someone who develops the belief that he’s a failure, for example, will view each mistake as proof that he’s not good enough. When he does succeed at something, he’ll chalk it up to luck.

Consider for a minute that it might not be your lack of talent or lack of skills that are holding you back. Instead, it might be your beliefs that keep you from performing at your peak.

Creating a more positive outlook can lead to better outcomes. That’s not to say positive thoughts have magical powers. But optimistic thoughts  lead to productive behavior, which increases your chances of a successful outcome.

Challenge Your Conclusions

Take a look at the labels you’ve placed on yourself. Maybe you’ve declared yourself incompetent. Or perhaps you’ve decided you’re a bad leader.

Remind yourself that you don’t have to allow those beliefs to restrict your potential. Just because you think something, doesn’t make it true.

The good news is, you can change how you think. You can alter your perception and change your life. Here are two ways to challenge your beliefs:

• Look for evidence to the contrary. Take note of any times when your beliefs weren’t reinforced. Acknowledging exceptions to the rule will remind you that your belief isn’t always true.

• Challenge your beliefs. Perform behavioral experiments that test how true your beliefs really are. If you think you’re not good enough, do something that helps you to feel worthy. If you’ve labeled yourself too wimpy to step outside of your comfort zone, force yourself to do something that feels a little uncomfortable.

With practice, you can train your brain to think differently. When you provide up those self-limiting beliefs, you’ll be better equipped to reach your greatest potential.

Amy Morin is a psychotherapist and the author of the bestselling book 13 Things Mentally Strong People Don't Do.