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Enter Tableau AI—the next evolutionary leap, simplifying data analysis to the point of asking a question. Powered by Einstein, Salesforce's AI, Tableau AI heralds a new frontier in effortless data exploration. Alongside this innovation comes Tableau Pulse, revolutionizing the data experience for all users within your organization, irrespective of their familiarity with data analytics.

Tableau AI

Tableau AI stands as a groundbreaking innovation, harnessing the advanced capabilities of generative AI to revolutionize and democratize the data analysis process. This next evolution of Tableau is grounded in the trusted and ethical foundations of Einstein, ensuring its reliability and safety for all users.
The true power of Tableau AI lies in its capacity to elevate every facet of the Tableau platform, driving performance, efficiency, and scalability to new heights.
Tableau AI empowers data analysts by automating analysis, preparation, and governance processes. It streamlines workflows, reduces technical barriers, and eliminates repetitive tasks. Using AI, it facilitates natural language calculations, suggests suitable visualizations, and generates data source descriptions.
Focused on aiding decision-making, Tableau AI distills meaningful insights from datasets, presenting them in plain language. It anticipates follow-up questions and helps break down data silos for effortless access to vital insights. Its conversational interface swiftly delivers essential insights, designed for both experts and non-experts in data analysis.

Tableau Pulse

Tableau Pulse introduces a transformative era in data interaction, making analytics accessible to everyone. Enabled by Tableau AI, this reimagined data experience is tailored for analytics consumers, delivering smart, personalized, and contextual insights seamlessly integrated into their workflow. It's a paradigm shift empowering every employee with the tools to make data-driven decisions effortlessly.
This evolution reshapes how individuals connect with data, fostering deeper, more meaningful engagements. Its goal? To elevate the entire organization, transcending the limitations of the 29% currently leveraging data for decision-making. Tableau Pulse is a game-changer, especially benefiting those pressed for time, seeking instant access to data for swift decisions, and desiring a deeper comprehension of the 'why' behind data, not just the 'how' and 'what.'
Experience the future of data interaction with Tableau Pulse, where insights become an inherent part of everyday workflows, empowering individuals across the organization to harness the full potential of their data effortlessly.

Streamline Your Focus with Metrics that Matter

Businesses grapple with vast volumes of information, often presenting reports in a standardized manner to accommodate entire teams. While this aids time-strapped analysts by minimizing the need for bespoke reports, it leaves end-users sifting through data to locate their relevant metrics—an arduous and time-consuming task.
Tableau Pulse revolutionizes this paradigm by seamlessly delivering personalized data summaries directly within your workflow. It introduces an intuitive, customized metrics homepage, allowing you to curate metrics aligned with your specific requirements. Say goodbye to the cumbersome process of filtering through multiple dashboards to find pertinent figures.

At the start of this example, Tableau Pulse presents a select set of metrics fitted to this specific user's focus.
These metrics are curated based on recent data trends identified by Tableau AI: Source: https://www.tableau.com/blog/tableau-pulse-and-tableau-ai
Towards the bottom of this example, Tableau Pulse showcases the KPIs that this user has actively tracked. Within this section, Tableau Pulse provides the most recent metric value, a brief visual representation of the trend, and an AI-generated insight specifically pertaining to that metric:

Source: https://www.tableau.com/blog/tableau-pulse-and-tableau-ai

Embed Relevant Data into Your Workflow

These days, professionals juggle various applications, which poses a challenge when tracking crucial KPIs. The continual shift between disparate tools not only consumes time but also disrupts workflow continuity.
Tableau Pulse heralds a transformative shift by integrating pertinent data directly into users' existing tools. This breakthrough ensures data detachment from specific dashboards, guaranteeing access to essential metrics without workflow interruptions. Insights are seamlessly captured within the tools where users spend the most time, eradicating the risk of missing critical information due to platform discrepancies. Additionally, this integration streamlines the scalability of insights across the organization, simplifying the process of visualizing, sharing, and collaborating on data by utilizing tools already familiar to everyone within the company.

Effortless Data Interpretation

Today's data interpretation can often entail a laborious and manual process. Users invest significant time analyzing data to unveil trends and insights while navigating the labyrinth of questions to pose to their datasets. This complexity invariably impedes decision-making speed and hampers overall productivity.
Tableau Pulse redefines data utilization by automating analysis and communicating insights in easily comprehensible, natural language formats. Initially, Tableau Pulse assumes the burden of uncovering the 'why' behind the 'what.' It autonomously identifies and generates insights, predicting the queries you might raise and even suggesting questions that may not have crossed your mind. Subsequently, Tableau AI succinctly summarizes these insights conversationally. This streamlined approach facilitates faster, informed decision-making, eliminating the need for extensive manual data analysis.
In the example below, Tableau Pulse extends its capabilities to address your data inquiries using natural language. Upon delving deeper into the "Appliance Sales" metric, Tableau Pulse was queried, "What is driving change in Appliance Sales?" In response, Tableau Pulse swiftly provided a concise answer along with a visual representation elucidating the factors influencing this change.

With the introduction of Tableau AI and Tableau Pulse, Tableau is set to revolutionize the industry once more, unveiling a fresh experience tailored for analytics consumers. This innovation aims to empower every individual to embrace a truly data-driven approach. Tableau AI and Pulse are reshaping how organizations engage with data, empowering decision-making, and fostering a more data-driven future.

When the sliver of thought -- that we have seen all that Tableau can do -- crosses our mind, just pay witness to a meteor shower of new features lighting the horizon up! Tableau is officially upgraded to 2021.3. Tableau 2021.2 was a remarkable update in itself: it included ‘ask and explain data’ for viewers, allowing connected desktops, Collections, and many more valuable options and features. So, what does the latest upgrade feature? In one go, the following list encapsulates the whole gamut of supplements:

1. Improvements to Data Prep Experience
   1. Linked tasks
   2. Generate rows
2. Improvements to Tableau Catalog
   1. Data quality warnings in subscription emails
   2. Inherited descriptions in web authoring
3. Slack Integration
4. Additional Features
   1. Customise the set of workbooks on the homepage
   2. Rename published data sources directly in Tableau Online or Server

Improvements to Data Prep Experience Tableau Prep, an indispensable backstage prior to staging your real and original data show, has found a high-power addition. With Linked Tasks in Tableau Prep Conductor, one can now bring enhanced harmony to his data preparation. Creators with Data Management or DM can now schedule flows to run one after the other on Tableau Online or Server. This feature has a wide range of applications; for instance, if the sales data for a designated time is yet to show up on the system and fails at source for some reason and there are multiple flows connected to that data source, stale data issues will unnecessarily pop up in all the workflows. With linked tasks, this issue can easily be prevented from manifesting. Linked Tasks on, it’s now simple to automate the orchestration of multiple flow jobs, ensuring they happen in sequence after each task completes successfully. Essentially, if your data didn’t update and there are two workflows linked to the same datasets at different time intervals, they both run, consuming time and resources; the scenario can be avoided, and the other linked task can be stopped from running; thanks to the new feature. A multitude of benefits come power-packed as the feature unfurls:

• Authors of a flow can get alerted automatically provided any of the jobs fail and can set up an appropriate warning on the data for consumers well in advance.
• Any flow can be scheduled by customers, or they can extract refresh to run when new data arrives, saving them time and resources.

Please see Image 1 to have a better understanding.

(Image 1: Linked Tasks on Tableau Prep)

Besides, Tableau Prep Conductor can generate a set of rows that are otherwise missing based on dates, date times, or integers. This is of huge importance as it allows users to fill gaps in data quite easily to ultimately ensure that processes downstream have all the requisite datasets to work on and create highly accurate and precise visualisations. Please see Image 2 for a quick understanding of the feature:

(Image 2: Generate rows on Tableau Prep)

Improvements to Tableau Catalog Next in the line comes improvements to Tableau Catalog. Two features need special mentioning:

1. Data quality warnings in subscription emails, and
2. Inherited descriptions in web authoring

Data quality warnings are of paramount importance. Accurate warnings, when they are around, lends confidence to the customers that the right, trusted data is being utilised to arrive at sound business decisions. Formerly, this was restricted to Tableau Online or Server, but now it is delivered straight into your inbox bundled with the subscriptions to the dashboards you care for. The power of data visualization with visibility into the quality of the data feed add top-notch credibility and renders confidence to the customer who spends a good portion of the day paying attention to emails. In the 2021.3 version, Data Quality Warnings are available in Web Authoring. This will soon be available in Tableau Desktop as well. Slack Integration Yes, Tableau notifications can now be directly accessed on Slack! Admins and Users will control what notification types can be dispatched on Slack. Notifications include:

• Shared content
• Data-driven alerts
• @mention

This is just the commencement of the Tableau + Slack integration. Other Stellar Features Up until the upgrade, the same three sample workbooks have occupied the Desktop Homepage of Tableau. They may give a good starting point for new users to get acquainted with Tableau. But the datasets were always generic and did not get updated. Now with the customizable set of workbooks on the home page, this has undergone a radical change. (See image no.3)

(Image no.3)

Add to this the ability to rename published data sources directly in Tableau Online or Server on the data source page; the upgrade is a real treat to data rockstars. (See image no. 4) Practitioners point out that The REST API can also be used when changing a large number of workbooks to minimise efforts.

(Image no.4)

No need to generate a newly published data source to change the name. No need to manually change all workbooks on the Desktop to use that newly published data source, which was highly frustrating! So, welcome to Tableau 2021.3. Let us uncomplicate and perpetually so! Co-Author : Rakesh Neelakandan

This has changed the way we interpret information by giving us a look into past insights but also to forecast future events, allowing us to make informed decisions.

Tableau 2021.2. includes ‘ask and explain data’ for viewers, allow connected desktops, Collections, and many more valuable features. Some of the key enhancements are listed below.

Collections provides a new format to organize content across your sites on both Tableau Online and Server into manageable folders. You may group item together from different projects and workbooks and you can reuse content in multiple contexts without additional storage or resources. Collections also makes it easier to share content around a central theme. For example, you can create a “Daily Sales” collection that includes dashboards with daily sales statistics, ETL data flow, data sources, etc.

Collections helps you congregate your data. You are given the leeway to create, explore and save your content privately. Another key feature of ‘Collections” is that users can create customized collections which are by default private. However, you are given the option to share the collection with any authorized users you choose to provide access to.

1) User Management Enhancement

In earlier versions, a subscribed user, deleted by an admin, was not erased from the system entirely. They were then classified as an 'unlicensed user'.

With version 2021.2, the subscribed creator will be deleted automatically when an admin deletes a user either via the UI or the REST API, without the extra step of reassigning the subscription ownership.

2) Ask Data Enhancements

Ask Data Lenses

A new feature introduced with this update is 'Ask Data Lenses'. It allows for easy data curation with defined columns and value synonyms and also provides suggested questions to allow for more inclusive data from a variety of sources.

(The update brings a new content type that is Ask Data Lenses, making it easy to curate data with the definition of column and value synonyms and suggested questions so you can better leverage existing published data sources.)

They are created alongside published data sources Ask Data use case(s) while maintaining the underlying data source as its own entity.

These 'lenses' are comparable to ‘views’. For those of you who are adept with SQL, where you can write selected statements specifically to extract the required columns, give definitions, whilst maintaining the integrity of the data source. Similarly, once created, ‘lenses’ can be accessed by viewers, opening Ask Data to a new class of users that struggle to self-serve their needs today.

Entity Search

Entity Search shows users search results of keywords, like the Google search box. Ask Data gives you word-by-word search results, giving you instant feedback on your data and what Ask Data can do. Ask Data will automatically choose the most relevant interpretation of your search and these search results help you build that input more effectively by selecting the right fields and values in the data set. Ask data learns from your selections to choose smarter defaults for future searches.

MFA allows users to easily add an additional layer of security to their accounts.

This feature unlocks the ability for Tableau Online customers who utilize native Tableau ID authentication to enforce multi-factor authentication (MFA) when their users sign into their sites. End-users can use applications like Salesforce Authenticator or Google Authenticator to perform additional verification of their identity when they log on to Tableau.

MFA makes it much harder for common threats like phishing attacks and account takeovers to succeed. MFA is one of the easiest and most effective ways customers can enhance login security and safeguard their business and data against external threats. Easily rename multiple fields in prep allows creators to transition seamlessly from web authoring to Tableau Desktop with a single click of a button. Creators will now be able to edit any workbook that they have permission to on Desktop. Prior to 2021.2, users had to manually change each header name. For example, if a user wanted to change “Customer” at the start of multiple header names, they would need to click on each field name and individually change/remove “Customer” in the field name. Not a big deal when there are less than 10 columns to update. However, for customers with data sets of 50+ columns, it is more cumbersome to have to individually change each field name. This feature allows a customer to quickly add a prefix, rename or add a suffix to multiple fields collectively. Tableau Prep is expanding its output capabilities to include Google BigQuery, enabling you to add or update data in Google BigQuery with clean, prepped data from your flow each time it is run. TABLEAU DESKTOP 2020.2 – Key Features 1) Maps: Spatial File Support The Marks Layers Control SP1 feature provides a control that allows users to toggle the visibility of layers on a map viz. The control works like a filter and the user is free to choose which layer(s) to view in order to answer their question. In addition, the user can control the interactivity of the map viz by selectively enabling or disabling selection on the layer in question. Toggle button – Our users can now use a button to show/hide any dashboard zone, floating or tiled. This function was previously limited to floating horizontal and vertical containers only. URL support for images – Users can now add images via external URLs, which also provides GIF support for images on the internet and workbooks. Loading these images will be time-efficient.

How User Roles and Permissions Facilitate Implementing Data Governance

The Alteryx Server helps enterprises implement effective data governance by ensuring every user operation is based on pre-defined user roles and permissions. It optimizes processes and access control and ensures data integrity. User Roles Defining user roles helps businesses ensure a safe and efficient analytics setting that aligns with best data governance practices. Each role assigned to users ensures they have the right level of access to perform their tasks. • Curator /Server Admin: Accessing the admin interface to run administrative tasks- crucial in enforcing governance policies. • Artisan: Publishing, running, and sharing workflows in their private studio and shared collections- ensures control over their workspace. • Member: Running workflows that are shared with them via collections – supports collaboration without giving excess control while adhering to data regulations. • Viewer: Running public workflows on the Server UI home page and in districts – ensures workflow integrity by limiting them to consumption roles. • No Access: No access to all Server assets- ensures data security for confidential data. User Permissions Besides user roles, you can set user permissions to decide what users can do in the Server UI. User permissions are paramount to upholding robust data governance and ensuring that users can only perform tasks within their scope of responsibility. • Scheduling workflows to run at a planned time – ensures timely task completion without manual intervention. • Prioritizing jobs to run those with the highest priority first- facilitates effective resource allocation and alignment with requirements. • Tag a specific worker to run a workflow- ensures resources are allocated right. • Create new collections within a defined structure- supports collaboration without risking data privacy. • Granting server API access to users- enables task automation without compromising governance • Allowing users to create or edit DCM assets- controls access to shared credentials and connections. • Sharing DCM Connection Credentials to run on the server- ensures data security, which is crucial for governance. • Sharing DCM Connection Credentials for collaboration- strengthens data governance by securely handling confidential and sensitive data. • Managing generic vaults- enables secure handling of credentials and sensitive data. • Blocking the user from accessing the Server UI- ensures that only authorized individuals can interact with sensitive data.

How to ensure Effective Data Governance?

For organizations to cater to their specific requirements, implementing and maintaining an effective data governance process is required, which is briefed below:  • Identifying the data assets of your organization. • Classifying your data based on significance and prioritizing data governance actions • Ensuring accuracy, completeness, and consistency of your data for efficient data quality management. • Safeguarding data from unauthorized access • Controlling data access, including giving and withdrawing access to data • Managing your organizational data throughout its lifecycle

Data Governance in Alteryx: Best Practices

The blog gives you a walkthrough of the best practices about how Alteryx handles data governance by ensuring data management and quality.

1. Authenticating and Authorizing Data: The initial aspect to address in data governance strategies is how data is accessed. Alteryx supports the existing safety measures implemented at the database level; it utilizes your username and password when connecting to your data. These credentials authenticate users and ensure they can only access the data permitted. Alteryx also supports pass-through authentication, facilitating access to data using network identity and authenticating users with the same credentials they use for access. It eliminates the need to manage separate usernames or passwords within Alteryx. In short, Alteryx easily integrates with your organization's existing security infrastructure, leveraging authentication mechanisms to ensure secure data access. 2. Managing Data Effectively: A standout factor in Alteryx's data management is that it does not require the creation of a distinct persistence layer for data storage during processing. The Alteryx server is designed to support multi-tenancy, using in-memory processing and handling temporary data in a sandboxed setting. This means that a single instance of an Alteryx Server can manage multiple workflows simultaneously. Different departments can use the same platform without the risk of unauthorized data access between them. 3. Tracking Data Lineage The drag-and-drop interface of Alteryx offers robust visualizations of the transformations occurring within the workflow. Organizations get a detailed knowledge of the data sources, how they are collected, prepared, blended, and analyzed, the workflows being run, and the count of records read and written. 4. Defining Data Ownership and Stewardship Establishing clear data ownership and stewardship and assigning responsibilities for data sets and workflows is important, especially in an environment like Alteryx where multiple users engage with data. Data ownership is about taking responsibility for the accuracy, privacy, and availability of a data set. Data Stewardship ensures data integrity and quality by implementing policies and ensuring proper documentation. Defining these roles clearly within the organization fosters accountability and reduces data misuse risk. 5. Leveraging Metadata and Data Cataloging Metadata is integral to comprehending your data's context and lineage. The Alteryx Connect tool helps handle metadata and build a centralized data catalog. Data catalogs allow users to discover available data easily, track where the data comes from, and enhance collaboration by sharing and reusing datasets and workflows. 6. Ensuring Data Security and Access Controls When using Alteryx, enforcing appropriate security measures ensures that only authorized users can access sensitive data. To minimize the risk of a data breach, Alteryx helps organizations by providing robust user access control options, supporting encryption of sensitive data, and establishing validating processes for workflows. 7. Monitoring Data Quality Data quality is paramount to effective data governance. Alteryx streamlines and automates data quality monitoring by: • Providing data profiling and validation tools to check for duplicates, inconsistencies, and missing values. • Utilizing Alteryx Server to schedule periodic audits, maintaining data integrity over time. • Setting up alerts or automated reports to notify data owners or stewards of any data quality issues that arise. Data governance is beyond data management. It extends to the policies and processes that decide how an organization should use data while aligning with its goals. With effective data governance, businesses can boost data accuracy and security, enhance efficiency, and boost business value by complying with regulations, tracking data quality, and eliminating discrepancies. With Alteryx's built-in capabilities and powerful tools, organizations can manage the multidimensional challenges of data governance.

Recognized as a leader in analytics and business intelligence platform for 9 consecutive years in Gartner Magic Quadrant, Tableau has a variety of options when it comes to analytics and visualizations and according to me, it keeps getting better and better with every update. The latest 2021.1 update comes packed with some impressive features and these are some of them that caught my eye:

• Einstein Discovery
• Quick LODs
• More Data Connections
• View Metrics
• Dashboard Extensions in Tableau
• Write to Excel in Tableau Prep
• Device Designer for Web Authoring
• License Improvements

Einstein Discovery After its acquisition by Salesforce, Tableau has been at the advantage of being able to leverage Salesforce capabilities. In this update, Tableau has introduced its integration with a powerful AI driven Salesforce product – the “Einstein Discovery”. With this feature, I can get smart predictive modelling capabilities for quick business decisions without any effort of creating complex codes or algorithm. Einstein Discovery has been rolled out in Tableau through three approaches, through dashboard extensions, through analytics extension, and through Tableau Prep which was released in version 2021.1.3. Although this feature requires an additional Einstein Discovery License, I find the end benefit totally worth it.

• Through Dashboard Extensions: To use “Einstein Discovery” in dashboards, I can just add an extension object on the dashboard and select Einstein Discovery. It will analyse the selected data and build predictive models. It shows me the top predictors in the view along with metrics that can be improved, and thus helping business decisions. This feature is available in Tableau Desktop, Tableau Server and Tableau Online.

• Through Analytics Extension: With this feature, I can directly embed predictions into Tableau calculated fields. All I have to do is go to Salesforce, use Model Manager to generate a Tableau table calculation script and paste the script into the calculated field in Tableau. This script then accesses predictive models in Salesforce by passing the data required for the model. This saves my time since I don’t need to create a code for the model. This feature is only available in Tableau Desktop and Tableau Server.

• Through Tableau Prep: This feature was released in 2021.1.3 and its ingenuity is worth mentioning. With “Einstein Discovery” in Tableau Prep, I can now use predictions while preparing data. I can bulk score my data and create fields to show prediction outcomes, to show top predictors and to show recommendations for improvement of the output.

Quick LODs LOD calculations are frequently used in Tableau to perform calculations on a fixed dimension. Where previously I had to mention the dimension to be fixed and the measures to be aggregated in a calculated field, now all I must do is select the dimension and measure in the data pane and right click to create an LOD calculation. Or even better, hold “Ctrl” to drag and drop the required measure field onto the dimension to be fixed. As simple as that. I can modify the calculation with more dimensions or change the type of aggregation later, if required. This feature is most beneficial as it reduces the chance of errors while creating complex LOD calculations, like misplacing a bracket, or adding any unnecessary characters by mistake. More Data Connections With the increase in popularity of Microsoft Azure services among users, Tableau has added multiple Azure connectors including Azure SQL Database and Azure Data Lake Gen 2 along with the existing Azure Synapse Analytics and Databricks. I can now connect to data that is stored in Azure’s SQL Database and Data Lake using the native Tableau connectors. Tableau has also introduced authentication to Azure services using the Azure Active Directory, making the connection more secure. In addition to this, four new data connectors have been added to Tableau Online and Tableau Server. They are Amazon Athena, Apache Drill, OData and SharePoint Lists. View Metrics A difficulty that I had faced with the metric feature was that I was not able to know the other metrics that were created in the same dashboard. With this update I can see all the metrics associated with a particular dashboard and modify these metrics if required or create new ones within the metrics pane. And previously, only if my site role were “Creator” or “Explorer”, I could see the metrics. But in this update, I can see all metrics connected to a dashboard irrespective of my site role. Dashboard Extensions in Tableau Earlier, to use an extension in a Tableau Dashboard, I had to drag and drop the extension object on the dashboard which would take me to its extension gallery web page and then I had to download it and then locate the downloaded extension on Tableau. Sounds tiring right? Not anymore! With this update, all I have to do is drag and drop the extension object onto the dashboard to select the required extension. I can now see all extensions and filter the list based on categories within the “Add an Extension” window in the Tableau screen. Write to Excel in Tableau Prep This is one feature that will prove useful to any regular Tableau Prep user. The days of exporting an output to csv and then converting it manually to an xlsx file are finally over. Using the latest version of Tableau Prep, I can directly export the output of a workflow into an xlsx file. Device Designer for Web Authoring Where before I could only generate device specific layouts in Tableau Desktop, now I can create custom phone or tablet views within the web itself. I no longer have to modify the device layout in Tableau Desktop and re-publish whenever a change in device layout is required. Licensing Improvements With this update, Tableau has introduced zero downtime licensing for the Tableau Server. Now for most of the tasks, whether it is the activation of a license or updating a feature that got added or applying some changes to user capacity, I no longer need to perform a server restart. So, these are some features that have been helpful to me and these are just a few of the lot. To view all the new features in 2021.1, you can view it at Tableau 2021.1 New Features In my view, Tableau has done a great job with its timely and inventive updates and seeing the rapid growth of AI and the increase of its application in numerous industries, I can predict for sure that Tableau will surprise the data science community with more innovative updates. Images Courtesy: Tableau