The context

There is a popular perception that a desktop job in IT is synonymous with ill health. As the pandemic swept the globe and knocked down everything on its path from lives to livelihood, the IT industry continued to prosper due to the explosive growth in the digital arena.

But it came accompanied with its own set of problems and challenges. Long working hours and sedentary lifestyle have taken its toll. The incidence of lifestyle diseases for knowledge workers went in tandem with the northward growth map of the IT industry.

The Beinex difference

Beinex was an exception to this rule; thanks to the fitness challenge it had initiated as a part of its Autumn Connect programme: a competition for its employees with a slew of challenges they took on enthusiastically from cooking healthy food to addressing fitness goals.

Beinex Planethon

In sync with this spirit, and to promote it further, Beinex conducted ‘Beinex Planethon’.

It was a jovial day for us, even as we had to report at the JNI premises by 6.30 AM. The morning was pleasant and by the time it became 7.00 AM, all of us had assembled at the flag-off location.

Shiny Justine and her daughter Surya Ann Justine flagged off the Marathon. Shiny Justine delivered an inspirational speech before the flag off. She exhorted the gathering to make fitness initiatives habitual. She spoke to us that it takes just a small percentage of our time to add to fitness and health and it prevents medical exigencies from popping up suddenly.

Post the marathon session she was awarded a memento as a token of our appreciation.

Let us do our bit. Now is the time to draw inspiration and make fitness a habit! Run for our health and yes, run for our planet.

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.

AWS: Four Types of Cloud Business Value

In the era of digital transformation and infrastructure modernization, the journey to the cloud has been both exhilarating and challenging. Many businesses have successfully migrated their "easy" applications to the cloud. However, a prevailing concern lingers among business leaders—an uncertainty about the returns on investment in terms of time and effort. Questions arise about productivity gains, data security, and the impact on critical agility metrics, such as time to market. Here, we delve into the distinct results observed by AWS users across four pivotal domains of cloud business worth: cost efficiency, workforce efficiency, resilience, and adaptability.

1. Cost Savings: More Than Meets the Eye

Migrating infrastructure to Amazon Web Services (AWS) yields significant cost savings, averaging around 20% in total infrastructure expenses. Top performers witness a staggering 47% reduction, highlighting the potential for substantial savings. Yet, the nuances lie in application-specific cost reductions that vary based on factors like application complexity and cloud tenure.

Studies reveal a significant financial shift for organizations venturing into AWS migration. On average, businesses witness a remarkable 20% reduction in total infrastructure costs—a noteworthy achievement translating to a staggering $69 million slashed from an average pre-migration annual IT spend of $345 million. However, the journey to AWS doesn’t merely stop at these impressive numbers. For top performers, the stakes are higher, yielding an exceptional 47% savings in total infrastructure costs. This equates to a colossal $164 million reduction from an average annual IT spend of $349 million. (Refer to Fig. 1 for a graphical representation.) Fig.1 Study participants also provided data for up to three specific applications transferred to AWS, allowing the calculation of cost savings specific to these applications. On average, infrastructure costs related to these applications witnessed a consistent decline of around 20% annually over a span of six years post-deployment. Following migration, the extent of cost reductions varies among different application types. Multiple factors influence this variability, including the complexity of applications, their level of modernization and optimization before and after migration, and their duration within the cloud. Notably, patience yields rewards in this scenario. Analysis of application costs based on their tenure in AWS demonstrates an incremental improvement in savings rates with each passing year. (Refer to Fig. 2 for a graphical representation.) Fig.2 Comparative analysis between cloud and on-premises deployments highlights a positive correlation between increased cloud adoption and various efficiency metrics.

Nearly 3X lower total cost for procurement functions compared to equivalent on-premises solutions.

A $0.24 decrease in HR costs for every dollar invested in cloud.

Labor cost reductions of 18% to 20% in both HR and finance.

A 4% increase in HR productivity (output) for every dollar invested in cloud.

A productivity increase of 7% to 12% in procurement.

Factors impacting potential cloud cost savings include baseline infrastructure costs, application types, duration in the cloud, and post-migration innovations. Organizations with high infrastructure spending can see a 41% reduction after migration compared to the 20% average. Additionally, AWS migration leads to a 23% cut in overprovisioned application capacity, optimizing efficiency and reducing unnecessary costs.

2. Workforce Efficiency

Following the migration of applications to AWS, there's a noticeable enhancement in IT infrastructure staff productivity among respondents. They report a remarkable 66% rise in the number of retained VMs managed per administrator. Such post-migration efficiencies enable a strategic shift, allowing 17% of staff positions to transition from routine infrastructure maintenance to pivotal roles focusing on infrastructure planning, architecture, orchestration, and innovation (Refer to Fig. 3 for visual representation)

Fig.3 Moreover, a substantial productivity boost unfolds within development teams post-AWS migration. There's a notable 29% increase in developer time dedicated to crafting new features and functionalities, shifting from minor updates handled by cloud providers. Leveraging AWS developer tools streamlines coding processes, further amplifying developer productivity. These enhancements result in a 32% average reduction in the time interval between production releases for migrated applications. This surge in productivity not only streamlines operations but also empowers organizations to overcome the barrier to innovation identified by respondents—the challenge of dedicating ample time to innovation amidst other pressing concerns.
A commercial finance organization exemplifies the tangible impact of AWS migration on innovation. Their technology division experienced a significant leap in developer focus post-migration. Initially allocating 20% of developer time to crafting new features, their shift to AWS elevated these efforts drastically. For customer relationship management and business intelligence, the focus surged to an impressive 60%, witnessing a threefold increase. However, the transformation was even more substantial for their migrated financial planning and analysis system, skyrocketing from a mere 20% pre-migration to a staggering 80% post-migration—showcasing an unparalleled fourfold increase.

3. Resilience

Cloud technology has redefined resilience by elevating system availability, reducing latency, and fortifying security measures. The disruptive impact of the pandemic accentuated the criticality of resilience, surpassing the effectiveness of traditional disaster recovery approaches and redundant data centers. Cloud-based infrastructure emerged as a crucial linchpin, ensuring uninterrupted operations during tumultuous times.
The scalability inherent in cloud services played a pivotal role during the pandemic, exceeding initial capacity plans by an astounding 90%. This scalability was instrumental in swiftly connecting and supporting remote workers, effectively mitigating disruptions. Chief Information Officers (CIOs) emphasized that their previous migration to AWS significantly facilitated the accommodation of sudden surges in demand, underscoring the importance of cloud infrastructure in maintaining seamless operations during critical periods.
A U.S.-based healthcare nonprofit's strategic migration of its last on-premises ERP system to the cloud in 2019 fortuitously positioned it for the subsequent shutdowns and challenges brought on by the pandemic. The seamless integration of cloud technology enabled the organization to navigate and maintain operational continuity amidst adversity, highlighting the indispensable role of cloud solutions in supporting mission-critical functions and adapting to hybrid office-remote work models.
In today's digital commerce landscape, system downtime carries profound consequences far beyond inconvenience. It significantly impacts businesses, directing customers towards competitors' platforms. The financial implications of downtime are staggering, averaging 79 minutes and costing approximately $84,650 per hour in 2020. Furthermore, the aftermath of data breaches and ransomware attacks extends beyond financial costs, causing public embarrassment and substantial recovery expenses, averaging $4.6 million for cyberattacks and $4.2 million for data breaches.
The migration to AWS represents a transformative milestone, significantly bolstering both availability and security. Many key resilience Key Performance Indicators (KPIs) exceeded the 50% mark, as illustrated in Fig. 4. This substantial enhancement underscores the transformative impact of AWS migration in fortifying operational resilience and proactively mitigating potential threats.

Fig.4

4. Adaptability

The most strategic of all cloud migration benefits, agility equips organizations for success in a digital business environment. Agility refers to the ability to respond quickly and effectively to changes in business conditions or disruptive business events. Broadly speaking, the more technology infrastructure an organization has in the cloud, the more agile it can be. A study by The Hackett Group on agility in business services functions (i.e., finance, HR, IT, and procurement), found that the most agile organizations have 41% of their infrastructure in the cloud, compared to just 29% for the average respondent.
Winning in a digitally competitive industry or market depends heavily on agility in product development. A major aspect is the speed at which new technology-enabled products and features are brought to market. For applications in the cloud, technology organizations are better able to use agile/DevOps methodologies thanks to services that simplify and accelerate provisioning infrastructure, deploying application code, automating software release processes, and monitoring application and infrastructure performance. These changes, combined with the development-team productivity gains discussed earlier, contribute to a 43% decrease in time to market and a faster pace for production releases (Fig. 5).

Fig.5

Recommendations

The Cloud Services Study underscores how migrating to AWS drives substantial business value across cost savings, staff productivity, resiliency, and agility. It dispels the notion that the cloud is solely a cost-saving venture, highlighting its strategic superiority over traditional on-premises infrastructure. The agility alone—enabling quicker time to market, enhanced insights, and frequent production releases—positions organizations competitively in the digital sphere. This transformative shift from infrastructure management to innovative development is a pivotal game-changer.
In forthcoming reports, we'll delve deeper into specific migration strategies and cloud financial management practices that contribute to superior outcomes. Meanwhile, here are key insights from this study:

Migration's financial benefits transcend infrastructure cost reductions. Anticipate increased efficiencies in application provisioning, reduced security incidents, minimized downtime, and amplified agility.

Optimize cloud costs post-migration. Implement strategies like consumption-based pricing and best practices in cloud financial management, leveraging tools like AWS Cost Explorer for uncovering cost-saving opportunities.

Cloud hosting should form a fundamental aspect of any digital transformation strategy. Prioritize migrating core applications and data to AWS to enable faster data access, insight generation, and expedited time to market, essential for competing in digitally advanced sectors.

Cloud serves as a crucial pillar for future workforce enablement. The accessibility and scalability of AWS-hosted data and applications support hybrid or digital workforces, characterized by constant mobility, adaptable headcounts, and seamless real-time access to highly secure systems.

The pandemic experience validated the efficacy of cloud-based infrastructure as a robust defense against catastrophic disruptions. Accelerated cloud migration should feature prominently in every business continuity investment strategy and resiliency improvement roadmap.

Bringing automation to data management is one of Tableau’s big focuses for this release, to help users get insights faster. Some key features that help with that are:

• Virtual Connections
• Centralized Row-Level Security
• Edit Published Data Source
• Parameters in Tableau Prep

Virtual Connections – Complete data source oversight in one place Virtual Connections provide users with a single centralized connection to store credentials and other connection information for a data source. It would easily connect to data as opposed to that of embedding it in all workbooks and data sources that use it. Along with greatly reducing the maintenance load, this feature enables us to create tables and share access while securing service account credentials, establishing Data Policies, and extracting data centrally. Virtual connections might sound like a published data source but in published data sources, database connection information (like credentials) is bundled with higher-level data modeling like joins, calculated fields, default properties, etc. So, any user who wants to create and share data models is also responsible for storing and sharing the connection information, even if they aren’t the best person to do so. Virtual Connections separate these two concerns into different objects so they can be owned and managed separately. Centralized Row-Level Security - Bring precision and agility to data protection In general, Row-Level Security (RLS) refers to filtering out rows of data at query time based on the current user's identity. Due to this, different users can view the same table, viz, or report and see only data they are authorized to see. RLS allows scenarios like having a regional manager only see sales created within their team, but not sales from another manager's team. Rather than implementing RLS individually on every Tableau workbook or data source accessing a sensitive table, virtual connections can be used to centrally define and manage data policies. These policies will be consistently applied across all connected Tableau Flows, Data Sources, or Workbooks that depend on that data. This gives granular control over data security while bringing flexibility to reuse data sources. Edit Published Data Source This feature makes managing data sources very effortless. Now we can create, edit and rename data sources directly in Tableau Server and Tableau Online, test the changes, and publish—all without leaving the browser. This streamlines the governance and metadata management. Parameters in Tableau Prep Parameters in Tableau Prep speed up and simplify tasks by enabling users to easily change data inputs, data outputs, and values used throughout a flow which makes reusing them much easier. Supported step types in 2021.4:

• Inputs /Outputs File path/File name
• Published data source name
• Calculated fields
• Filters

Copy and paste in dashboards Another feature that needs a special mention is Copy and paste in dashboards. Now users can easily copy images, text boxes, and web page containers within the same and across different dashboards and workbooks in Tableau Online, Tableau Server, and Tableau Desktop. Through this, one could develop customized and interactive dashboards rapidly by recreating the already formatted items. Tableau 2021.4 Highlights

1. Data Management
   1. Virtual Connections
   2. Centralized Row-Level Security
2. Tableau Catalog
   1. Inherited column descriptions
   2. Create flows from Catalog pages
3. Tableau Prep Builder
   1. Tableau Prep Parameters
   2. Create Tiles
   3. Flow output Subscriptions
4. Tableau Online
   1. Connected Apps
   2. Tableau Bridge Multi-Pool
5. Analytics
   1. Metric Updates
      1. Show Metric status with colors
      2. Customize comparison period and data window
      3. Embed metrics
   2. Replay Animations
   3. Web authoring improvements
      1. Edit published data sources on Server and Online
      2. Copy/Paste Dashboard Zones
   The journey towards unveiling the full potential of data analytics can be experienced in a better way with this new adoption of Tableau. Guaranteed to make your work polished and effortless, Tableau 2021.4 opens up its myriad capabilities to help you derive meaning out of data. Let all the tech geeks armor up to savour the essence of this exciting update.

The concept of a sovereign cloud is not novel at all. Due to shifts in the geopolitical landscape and new legislations that have affected data control, it has recently become a hot topic. In a sense, the sovereign cloud offers a clever answer to a global conflict over digital sovereignty. Let’s delve a little further into it

The need for cloud sovereignty has, in turn, initiated the idea of digital sovereignty. This is all about data: who controls it, where it resides, and where it flows to. These inquiries are crucial in the modern data economy, where data is the new currency. Cloud services inevitably receive attention. They serve as the data economy's driving force.

The rules set for data sovereignty have been in place for several years in many nations, and new privacy laws like the General Data Protection Regulation (GDPR) emphasise their importance. For instance, countries like Russia, China, Germany, France, Indonesia, and Vietnam demand that citizen data be kept on servers within the country. The justification is that protecting citizens' personal information from misuse is in their best interests, especially outside a country's jurisdiction.

According to reports, global spending on cloud services is anticipated to reach $1.3 trillion by 2025, representing a growth rate of almost 17% annually. The pandemic's push to move more operations to the cloud to accommodate an increase in the demand for remote work is undoubtedly accelerating this growth.

But lately, cloud sovereignty is under closer scrutiny as enterprises and governments work to reduce their external exposure and maintain control over crucial resources in the light of escalating international conflicts, evolving data protection laws, and the dominance of certain cloud operators.

What can decision-makers do to manage this complex issue? Reports suggest a four-point plan; define, assess, align, and develop: 1. Define: Examine cloud service providers from the perspective of sovereignty, considering data sovereignty (for data residency, controls, transparency, storage, backups, etc.), operational sovereignty (for security, compliance, and operational resilience), and technical sovereignty (to evaluate integration, migration features, and a straightforward exit policy/ process). 2. Assess: Set up your cloud infrastructure to be flexible: choose the most practical of use cases and sensitive workloads; think about crucial management solutions and end-to-end encryption. 3. Align: Analyse hybrid options simultaneously and prepare for a multi-cloud architecture by being aware of its advantages and disadvantages. 4. Develop: Explore the value proposition of sovereign cloud in terms of trust, security, and cooperation through ecosystem engagement to maximise its potential.

Data sovereignty in the cloud reveals a complex environment; thus, it is wise for businesses to be informed and compliant. Here are three strategies or approaches for doing this.

1.Focus on the cloud

Maybe the answer to data sovereignty is in the cloud itself! Data sovereignty is an essential factor, even while the major cloud providers, such as AWS, Microsoft, and others, credit adoption rates based on customers' focus on price, availability, and flexibility. Most IaaS providers have local data centres, allowing for the fulfilment of the first condition. Additionally, crucial features like encryption and other available security-as-a-service choices enable users to adhere to regional laws.

One critical note of caution: It is crucial that the appropriate enterprise stakeholder comprehends the data protection laws of each country and evaluates and applies the required management tools provided by each supplier to comply with these laws.

With the rise of the Chief Data Officer (CDO), the company now has a responsible individual who must make sure the cloud provider has responses to the following questions in the contract:

1. Regulations governing privacy compliance being followed
2. Optionality for data location and recommendations based on performance, cost, and compliance; and
3. Methods for data encryption, key management, backups, and recovery

2.Emphasise consistency

Businesses should consistently follow even the most burdensome of regulations. Maintaining compliance with the data sovereignty regulations of each region in which an organisation conducts business is a constant problem for organisations with a worldwide presence.

The strongest of these regulations should be applied uniformly throughout all regions, regardless of what other areas require, as this will help to decrease complexity. In this, the cloud can be helpful. Choose a cloud provider that offers these features; often, the more prominent providers and those that concentrate on specific business verticals are the best.

Even the tightest restrictions cannot guarantee data security due to the growing instances of data incursions caused by breaches by third parties, such as partners, contractors, and software libraries.

Governing systems adhering to legal requirements and open to continuous policy modifications are crucial.

3.Use the cloud to implement data governance

Although the cloud provider might offer capabilities for data sovereignty, applying and updating policies on top of the tightest laws help limit risk. A thorough data governance strategy ensures adherence, ongoing risk assessment, and risk mitigation are always maintained. To do that, follow these five steps:

Discoverability: Define and control your cloud data. Quality control: Make sure domain and data sharing are followed. Compliance: Update policies on top of stringent regulations to help limit risk. Access: Access to administrators is monitored, automated, and managed; prompt customer, partner, and compliance responses are given. Lifecycle administration: Control the generation, distribution, storage, and deletion of data.

Laws and regulations governing data sovereignty are expanding in scope and complexity daily. The use of cloud infrastructure is multiplying, and the data deluge remains unabated. Together, these three provide some significant obstacles. However, businesses can advance and maintain their lead with a small initial investment and continual process implementations.

In the future, the CDO's responsibilities will continue to change and converge with those of the CIO, CISO, chief privacy officer, legal, and other roles. The organisation will be less vulnerable to risks if it can adapt by staying ahead of the data sovereignty regulations and developing robust data governance frameworks for the cloud.