Tableau Server Health Check: Ensure Peak Performance for Your Tableau Environment

But this does not apply to a slicer visual, which only has cross-filtering and no interaction feature. This made me wonder if we can achieve cross-highlight with a slicer visual through some work-around that allows me to compare one category with other easily through cross-highlight. After some research, I may have found a way to do this. Below are the steps in detail to achieve this. Normal filtering of data with slicer: The below example shows normal slicing of data where only the selected value will be reflected in the bar chart. This does not allow me to compare other values easily or focus in on the selected value through highlighting. Dynamic highlighting with Slicer: The below example shows the dynamic highlighting where I can choose the categories in the slicer to highlight for comparison with the other categories. I can easily focus on the selected categories and compare the measure values with other categories. Solution: First, I have created a disconnected table with the categories. This can be easily done with the following dax formula.

Selected Category = VALUES(Orders[Category])

Had made sure there is no relationship in the model view between the source table and new category table. Created a measure which will be added to the conditional formatting in data colour section in the format pane.

Selected Colour bar = 
var selected_category = VALUES ('Selected Category'[Category]) 
var category_to_highlight = SELECTEDVALUE (Orders [Category])
var filtered = ISFILTERED ('Selected Category'[Category])
var result = 
    SWITCH(TRUE(),NOT(filtered),"#0055cc", category_to_highlight in selected_category && filtered,"#0055cc","#9cd0ed")
return result

Explanation: Selected Colour bar =

var selected_category = VALUES ('Selected Category'[Category]) // taking values from category table

var category_to_highlight = SELECTEDVALUE (Orders [Category]) // Using selected value function 

var filtered = ISFILTERED ('Selected Category'[Category]) // checks if the column is filtered and will return true or false

var result = 
SWITCH(TRUE(),NOT(filtered),"#0055cc", category_to_highlight in selected_category && filtered,"#0055cc","#9cd0ed") 

/* The first condition checks if the there is no filtration will return all values, Then will be checking if the selected set of values is contained in the category column. The selected value will be returning a specific dark colour while the unselected value will be giving a lighter colour. */

return result

Created a bar chart with total sales given in the value section and the category column from the source data will be given as axis. Gave the highlight effect by adding a measure in the field value section of the data colour conditional formatting. Added the measure in the field value section. Added category slicer from the Selected Category table Finally arranged them and saw the magic happen. Conclusion: This goes to show the hidden features of Power BI one can explore with a little bit of tinkering with a dash of DAX. This blog is a first in a series of many nifty blogs. Hope you like it and looking forward to your feedback.

The digital transformation uses digital technologies to transform businesses’ operations, deliver customer value, and compete in the market. For SMBs, digital transformation can provide a pathway to growth, unlocking new potential for efficiency, productivity, and innovation.

The Context and the Harvest Potential

Reports suggest that SMBs that are digitally engaged can increase their profits up to twice as fast as their offline counterparts. Digital transformation opens up new market opportunities for SMBs, driving overall growth.

Some noteworthy figures include the expected economic value of digital transformation to reach $100 trillion by 2025. While 21% of organisations believe their digital transformation efforts are complete, 87% of senior business leaders consider digitalisation a company priority, with 79% of corporate strategists indicating that it is reinventing their business and creating new revenue streams.

Moreover, 71% of leaders believe that the role of the workforce is crucial in implementing digital transformation, as employees play an essential part in driving and adopting new technologies.

How to Get Started?

To commence the digital transformation process for your SMB, you should initiate a discussion with your team regarding the concept of digital transformation and how it will impact your business. Additionally, it is crucial to consider a few points, such as:

• Identify the areas where your business is falling behind compared to your competitors.

• Determine which components of your current business plan require replacement or technological advancement.

• Evaluate the operations that are time-consuming and can be automated

Here are some key pathways in which SMBs can unlock their potential through digital transformation:

1. Embracing Cloud Computing

One fundamental way SMBs can unlock their potential through digital transformation is by embracing cloud computing. Cloud computing has become a game-changer for SMBs, providing access to powerful tools and technologies without significant upfront investment. With cloud-based solutions, SMBs can scale their operations, reduce IT costs, and gain the agility needed to compete in a fast-paced market.

Cloud computing provides SMBs access to various services, including storage, computing power, and software applications, all delivered over the Internet. Using cloud-based services, SMBs can eliminate the need for on-premise IT infrastructure, reduce maintenance costs, and free up resources to focus on core business activities.

Cloud-based solutions also offer SMBs the flexibility to scale their operations quickly and efficiently. With cloud computing, SMBs can easily adjust their IT infrastructure to meet changing business needs, whether adding new users, increasing storage capacity, or rolling out new applications.

2. Leveraging Data Analytics

Data is the lifeblood of modern businesses, and SMBs can harness the power of data analytics to gain insights into customer behaviour, market trends, and operational performance. By leveraging data analytics tools, SMBs can make more informed decisions, improve processes, and identify new growth opportunities.

Data analytics tools can help SMBs to:
• Monitor customer behaviour and preferences
• Identify trends and patterns in sales data
• Optimise pricing and inventory management
• Improve marketing effectiveness
• Enhance operational efficiency

To leverage data analytics effectively, SMBs must have the proper data management and analysis tools. This includes collecting, storing, and analysing data from various sources, such as customer relationship management (CRM) systems, sales data, and social media metrics.

3. Automating Business Processes

Automation has revolutionised how businesses operate, and SMBs can benefit from automating routine tasks and processes. Automation can help SMBs to reduce costs, increase efficiency, and improve customer satisfaction by freeing up resources to focus on higher-value activities.

Automated processes can include:
• Invoicing and billing
• Inventory management
• Payroll processing
• Customer service
• Marketing and sales

By automating these processes, SMBs can reduce errors, improve productivity, and deliver a more consistent customer experience. Automation can also free up resources to focus on more strategic initiatives, such as product development and business expansion.

4. Embracing E-commerce

E-commerce has become a vital channel for SMBs to reach customers and generate revenue. By embracing e-commerce platforms, SMBs can expand their reach, reduce overhead costs, and offer customers a convenient, digital-first experience.

E-commerce platforms provide SMBs with a range of benefits, including:
• Access to a global customer base
• Reduced overhead costs
• Increased sales and revenue
• Improved customer experience
• Flexibility and scalability

To remain competitive in the digital marketplace, SMBs must adopt online marketing strategies and cloud-based solutions for operational efficiency. Moreover, customer-centricity is the primary focus in the digital market, unlike the traditional profit-oriented approach.

Summing Up

The scope of digital transformation is vast, and there is much more to it than meets the eye. Studies show that 85% of decision-makers feel digital integration is necessary within two years or less.

As such, the future of digital transformation will feature technology at the heart of all business processes and prioritise customer satisfaction. However, there will be significant challenges regarding needing more resources and skills, which business leaders must address and mitigate.

Beinex Digital, a part of Beinex Holdings, is a digital transformation entity with a comprehensive suite of independent products that address specific business gaps, use cases, and needs. The growth strategy of Beinex Digital revolves around inducing digital transformation as a way of life for businesses worldwide.

Rather than waiting for change to happen, businesses should start acting. The question is, are you prepared to embrace digital transformation?

What is Spatial Analysis?

Spatial analysis is the art and science of extracting insights from data that has a geographic component. Think of it as giving your data a physical address! Traditionally, this involved complex Geographic Information Systems (GIS) software. But today, spatial analysis is more accessible than ever, thanks to data science and machine learning.

Pinpointing locations on a map is just the first step. Spatial analytics goes far beyond that, offering a powerful lens to understand how relative location impacts your business. It allows you to see the bigger picture: how customers, stores, services, and other factors interact with each other geographically.

This magic happens by blending spatial data (think zip codes, store addresses) with your existing data sets (sales figures, customer demographics). By analyzing these combined datasets, you gain a wealth of insights that can transform your decision-making process.

What Spatial Analytics Can Do for You

Here's how spatial analytics can help you understand and optimize key areas:

• • Customer Behavior and Inventory: Analyze nearby consumer buying habits for specific products and services. This allows you to customize inventory and service experiences at each location based on local demand.
• • Strategic Location Planning: Optimize your location strategyby determining how the proximity of competitors or existing locations impacts new site expansion. You can also understand how far customers are typically willing to travel for your product or service.
• • Improved Customer Experiences: Ensure service availabilityand minimize service gaps by strategically locating key hubs within an appropriate distance from each other. This translates to a smoother and more efficient experience for your customers.
• • Targeted Marketing: Drive efficiencies in your marketing programs by customizing your offerings to match demographic purchasing preferences in specific locations. This targeted approach allows you to reach the right audience with the right message.

How Alteryx Enables Data Blending for Spatial Analytics

Forget complex GIS! Alteryx's no-code tools make spatial analysis a breeze, unlocking location intelligence for all data users. Optimize resources, plan assets, manage logistics, and more - all in a user-friendly platform.

Alteryx offers an intuitive workflow that streamlines the entire process:

• • Import and Unify: Easily bring in various datasets, regardless of format.
• • Effortless Geocoding: Transform addresses and other location data into usable geographic coordinates with a few clicks.
• • Spatial Blending: Combine your location data seamlessly with traditional datasets for a holistic view.
• • Advanced Analytics Made Simple: Perform complex spatial analyses without needing specialized coding skills.
• • Data Enrichment: Boost your insights by adding demographic, firmographic, or industry-specific data to your spatial datasets.
• • Visualize and Explore: Discover hidden patterns and relationships through interactive maps and visualizations.

A 6-Step Recipe for Blending Spatial Data in Alteryx

Alteryx makes blending spatial data with your existing information a breeze. Here's a step-by-step guide to get you started:


• • Gather Data: Gather all the data sets you need for your analysis, from customer information to market demographics.
• • Translate Your Addresses: Use Alteryx's geocoding tools to transform addresses and other location data into usable geographic coordinates.
• • Define Your Trade Zone: Create a virtual boundary to analyze specific locations based on radius
• • Blend Datasets Together: Seamlessly combine your spatial data with traditional datasets to create a comprehensive picture of customer-location relationships.
• • Use Advanced Spatial Analytics for Additional Insights: Perform complex spatial analyses within Alteryx's user-friendly interface, unlocking hidden insights without needing specialized coding skills.
• • Visualize and Share Your Findings: Prepare your data for reports and interactive visualizations that effectively communicate your insights. Alternatively, export the data for further analysis or integration with downstream processes.


Find a detailed 6-step guide for blending spatial data using Alteryx:


1. Gather Data

Alteryx's Input tool lets you grab data from anywhere – spreadsheets, databases, even social media! Just connect to your desired sources, and Alteryx will get your data ready for spatial exploration.

2. Turn Addresses into Locations:

The Street Geocode tool in Alteryx quickly transforms your standard addresses (like customer locations or branch sites) into geographic coordinates (latitude and longitude). This "spatializes" your data, adding a new data point for each location. In this example, we'll use it to geocode both customer and site data.

3. Define Your Trade Zone:

The Trade Area tool lets you see what's happening within a specific area around each location. For example, you can create a 10-minute drive time polygon. This "draws" a zone around each location, encompassing all areas reachable within a 10-minute drive using the road network.

4. Blend Datasets Together:

The Spatial Match tool lets you see how different sets of locations relate to each other. For instance, you can use it to find out how many customers live within (or outside) the 10-minute drive time zone you created for each location. It essentially compares your customer data points (spatial points) with the trade area polygons (spatial objects) to identify matches based on spatial relationships (like "contains" or "intersects").

5. Use Advanced Spatial Analytics for Additional Insights

Alteryx offers a range of additional tools for advanced spatial analysis, making it accessible to users beyond data specialists. Additional tools include:

6. Visualise and Share Your Findings:

Alteryx doesn't just help you crunch data - it enables you to share your insights clearly.

Visualize Your Success: Overlay data on detailed maps or satellite imagery using advanced mapping tools.

Spread the Knowledge: Export your analysis in various formats like Excel, ESRI, or even Tableau and Qlik for seamless integration with other data workflows and presentations.

Beinex + Alteryx Offerings

As a Premier Alteryx partner, we have extensive experience and a proven track record of success. Our team is highly skilled in Alteryx solutions and can help you unlock the full potential of this powerful platform.
Contact us today to learn more about how Alteryx and our partnership can take your business to the next level.
Image Source: https://community.alteryx.com/pvsmt99345/attachments/pvsmt99345/general-discussions/2303/2/Spatial_Cookbook_Victa.pdf

Snowflake summit 'The World of Data Collaboration' was held in Las Vegas, Nevada, June 13-16, 2022. It featured the first look at innovations coming to the Data Cloud. Over 200 lectures, practical labs, certification possibilities, and more than 200 Basecamp partners were included in the four-day data Snowflake Summit. Thousands of Snowflake's partners, clients, and industry colleagues were there to network, cooperate, and learn crucial information about Snowflake and new Data Cloud trends.

Here are the four most exciting of Snowflake's latest offerings:

1.Innovative data capabilities that save time and resources

The release of Snowpark for Python, which is currently in public preview, was one of the statements that received the most attention at the summit. Both streaming ingestions using the new Snowpipe Streaming and streaming pipelines with the launch of Materialised Tables generated a lot of interest. These new features demonstrate Snowflake's product philosophy, which strongly emphasises simplicity for partners and customers while delivering value. The declarative model is excellent since it only requires describing the change; Snowflake will handle the rest. They anticipate less data lag, more real-time features, and quicker decision-making.

A new workload, Unistore, that enables users to work seamlessly with transactional and analytical data together in a single platform stirred curiosity in the audience. Unistore can save time and effort in moving data from operational systems and help with low-latency machine learning (ML) inference scenarios. It provides snappy user interfaces, allowing teams to create real-time analytical queries on their transactional data and build transactional business applications directly on Snowflake and offers a unified approach to security and governance.

2.Creating, monetising, and using apps on the Data Cloud

The most intriguing news is the potential of the Snowflake Native Application Framework, which is now in private preview. Anyone may now create applications using the well-known Snowflake core functionality, share and earn money from them through Snowflake Marketplace, and deploy them directly inside a customer's Snowflake account. Customers may keep their data centralised and greatly simplify application acquisition and maintenance. In contrast, application suppliers will have quick visibility to thousands of Snowflake customers globally across the three major clouds. It was a piece of ground-breaking information for all parties.

Bidirectional and multi-source native apps developed by Informatica allow users to combine data from various cloud and enterprise platforms, including IBM, Microsoft, Salesforce, and SAP. So, Snowflake partners and customers can concentrate more on what to build and less on how to build it; Snowflake wants to make the building process more straightforward. Snowflake may not be able to foresee the entire extent of value creation and innovation that would result from this.

3.More options and cloud compatibility

As a customer-focused business, Snowflake constantly strive to strike a balance between giving our consumers options, streamlining processes, and lowering complexity. Providing a consistent user experience and simple governance for data housed in any of the three significant clouds is a crucial objective (AWS, Azure, and Google Cloud). With the help of the Snowflake platform, businesses may create their applications once and deploy them across several major cloud vendors' regions. Companies can migrate data—and now applications—easily between regions or clouds thanks to Snowflake's cross-cloud capabilities. You can use transactional consistency for failover and failback. For both customers and partners, Snowflake is offering a way to make the construction of cross-regional and cross-cloud experiences simpler.

Snowflake's ability to develop an app once and have it function flawlessly across various clouds and locations is a game changer. By enabling the Data Cloud to process data from S3-compatible storage systems, such as on-premises storage providers, Snowflake has also improved choice (currently in development). It also supports interoperability and open file formats as agents of choice. To that aim, Snowflake unveiled the presently under story Apache Iceberg Tables, which will let users select Iceberg as the persistence table type and Parquet as the file format, table by table.

4.Rich data experiences without sacrificing readability for data governance or security

Clients of Snowflake value the data governance and security provided by Snowflake as well as the release of numerous new features and enhancements are appreciated. For instance, with the assistance of Snowflake's new workload Cybersecurity, cybersecurity teams can easily break down data silos, resulting in improved visibility into security incidents, risks, and threats. In short, clients want to create reliable data products and openly share data without relinquishing control of or re-siloing their data. Snowflake accelerates the economic value cycle for partners, clients, and, quite honestly, by doing away with the trade-off.

Snowflake has planned to offer more services connected with data sharing, collaboration with clean data rooms, and Native Applications Framework.

Beinex's partnership with Snowflake

Beinex's partnership with Snowflake enables it to offer clients advanced features like automated tuning and elastic compute with unlimited decoupled computing capability, along with the analytics modernisation services, to help organisations realise exponential Return on Investment. We keep innovating for all our clients and to support businesses around the world to create more possibilities and quality services.

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