TABLEAU 2020.3 NEW FEATURES – TOP PICKS

The world expects a financial meltdown soon, and everyone has rolled up their sleeves to face it. Recession impacts are like separating rice from its husk; it differentiates winners from losers. Even if it is going to be a rocky year, companies should take it as a wake-up call to adopt new strategies and invest in digitalisation to move ahead.

During the pandemic, digitally advanced companies won a massive market share compared to those lagging in adopting digital transformation. They managed their supply chain and managed to sell through online platforms. It shows that the winners were better equipped, and they invested in facing the future. The pandemic revealed to us a guideline on how to be prepared and how we should respond.

The 2023 Gartner CIO and Technology Executive Survey reports that EMEA CIO business priorities for the remainder of 2022 and next year are growth and digital transformation, with the top areas of increased spending in 2023 including cyber and information security (70%), business intelligence and data analytics (53%), and cloud platforms (48%). Approximately 34% are increasing investment in artificial intelligence (AI) and 24% in hyper-automation as well. https://www.cio.com/article/411566/

How does digital transformation aid during an economic meltdown?

Risks are a common scenario for all kinds of businesses, and minimising risks equals future-proofing your organisation from a significant fall. But how? Through digital transformation, companies enhance consumer experiences, expand digital products, and build brand equity. Companies’ technologies ready bounded on their digital journey by investing in robotic process automation or cloud-based information management technology is sure to reap benefits. Digital initiatives can help to:

• • Manage interactions with clients, projects, and engagements.
• • Cut down on labour-intensive tasks through automation
• • Automate client or customer services
• • To make faster decisions and increase operational efficiency
• • Create a stronghold for information security
• • Develop new products and services
• • Generate a competitive advantage

Major Goals of Digital Transformation

Enhancing Operational Efficiency

Production, marketing, finance, accounting, and other processes are becoming more streamlined and trustworthy because of digital transformation. Digital marketing is becoming considerably more effective due to modern business technologies that enable it to get, analyse, and change crucial data for marketing and other uses.

Faster Decision Making

Most of the time, companies benefit from big data by placing data analysis methodologies at the core of their digital transformation strategy. To make the most of it, this data can be exploited by robust tools and turned into crucial business information. For targeted marketing campaigns and SEO plans, these outcomes can be utilised. With the help of a fully integrated digital transformation making decisions are simple.

Enabling Business Transparency

A company's potential to streamline business operations depends on effective transparency management. Since firms now use new communication channels to create transparency between higher authorities and employees, they can better disrupt the conventional working structure owing to digital transformation. Companies need digital platforms to assign responsibilities and assist them in running businesses. Examples of digital breakthroughs that help with effectively managing corporate transparency include analysed data, forecasting models, and online customer support services.

Driving Digital Transformation Amidst the Upcoming Downturn

CIOs can adopt three effective tactics to move forward with digital initiatives: empowering the workforce, ensuring financial and sustainable growth, and by implementing a robust cybersecurity system.

Empowering the Workforce

Repetitive and time-consuming tasks can be automated to create a more engaged employee group. Tools and technologies using AI can unburden employees, increasing their productivity and capability. Companies can experiment by incorporating online and onsite working modes to stay ahead of the pack.IT and HR can go hand in hand together to provide an elevated employee experience, resulting in a high employee retention level.

Adopting Intelligent Connected Infrastructure

AI, IoT, the cloud, analytics, and edge computing are all blended by Intelligent Connected Infrastructure (ICI) to share data among infrastructures, such as bridges, highways, and ports. Investing in ICI will boost commercial and societal progress while enhancing citizens’ quality of life. Implementing an Energy Management and Optimisation System (EMOS) to reduce energy usage can help to face future challenges and convert that into revenue sources. The strategy of blending finance and sustainability helps to win over customers, employees and investors.

Implementing a Robust Cybersecurity System

Cybersecurity is a rising concern for all enterprises, and not investing in it can invite risks. Developing threat intelligence platforms to prioritise and address cyber security threats is a measure to keep away from vulnerabilities. Continuous monitoring and comparing protection levels with other companies reduces the threat rates.

Summing Up

The future is unpredictable, and so are the risks, but businesses should be well-prepared to face it by taking strategic initiatives for technological developments. Past experiences proved that investments in technology wouldn’t go astray and can reap profits even at times of uncertainty. Recent research advises CIOs should not shy away from changes and be prepared with a roadmap to face macroeconomic uncertainty with digitalisation.

Beinex Offerings

Beinex Digital, a part of Beinex Holdings, is a digital transformation entity with a comprehensive suite of independent products focused on addressing specific business gaps, use cases, and needs. It incorporates a spectrum of solutions related to employee health and safety, enterprise product management, performance management, and audit & risk management.

To know more about us: https://beinex.com/beinex-digital/

This significant milestone reflects our unwavering commitment to delivering the best solutions to our customers' data challenges. With this enhanced partnership, we are poised to offer our customers unparalleled opportunities to leverage Snowflake's unique architecture and revolutionise their data-driven strategies.

Beinex: The First Snowflake Premier Partner in the Middle East

Beinex is the first Data & Analytics firm in UAE to enter Snowflake Services Partner Premier Tier. Beinex's exceptional service quality and the expertise of its consultants, scientists, and engineers have been demonstrated through years of unparalleled dedication to clients. The partnership between Beinex and Snowflake is set to revolutionise how businesses unlock the true power of their data.

The New Status Helps Us Serve You Even Better!

Snowflake's cutting-edge cloud data platform has garnered widespread recognition for its ability to deliver unmatched performance, scalability, and ease of use.

By attaining the Premier Tier Partner status:

1. Beinex can further leverage Snowflake's advanced capabilities and integrate them seamlessly into your solutions.
2. Enable and empower Digital Transformation at an accelerated pace for our clients with experience and competency of the right kind in accompaniment.
3. Aid our customers with the tools they need to extract maximum value from their data, propelling them towards success in an increasingly data-centric world.

Snowflake's architecture utilises a cloud-native approach, separating storage and compute, which results in unparalleled flexibility and scalability. This means that businesses can dynamically scale their computing resources as needed without the limitations of traditional on-premises solutions.

By embracing this architecture, our customers can say goodbye to lengthy and resource-intensive data processing times, paving the way for faster time-to-insights and improved operational efficiency.

Beinex+ Snowflake

The collaboration between Beinex and Snowflake has opened a new realm of possibilities for our mutual customers. The clients are further assured of the superior knowledge and competence possessed by Beinex’s league of Data Engineers, Data Scientists and Consultants in all matters Snowflake.

Now, organisations can experience a quantum leap in their data processing capabilities by harnessing the power of Snowflake's unique architecture. The ability to process vast amounts of data with lightning speed enables businesses to derive real-time insights and confidently make critical decisions.

Our partnership with Snowflake enables us to offer you advanced features like automated tuning and elastic compute, along with analytics modernisation services, to help your organisation realise exponential Return on Investment.

A Major Milestone for Beinex

The attainment of Snowflake Services Partner Premium Tier marks an exciting milestone for Beinex. This partnership underscores our dedication to delivering exceptional data solutions and reinforces our commitment to staying at the forefront of industry advancements. Together, Beinex and Snowflake are primed to transform how businesses harness their data's true potential, driving innovation and success in the digital era.

In this data-driven world, enterprises are dependent on humongous quantities of data that are subsequently analysed to uncover trends previously hidden and to carry out business functions. New tools, techniques, and technologies like those of Business Intelligence, Advanced Analytics, Machine Learning are used to analyse data and devise insights-informed strategies.

Also, they help entrepreneurs by guiding them to plan day-to-day operations, ensure fast and accurate reporting, increase revenue, identify new revenue streams, identify revenue leakage…the list is virtually endless.

Gartner explains Advanced Analytics as an autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools to discover deeper insights, make predictions, or generate recommendations. It uses Machine Learning, Artificial Intelligence, Predictive Analytics, Data Visualisations, and Text Mining to examine large data sets.

In fact, Advanced Analytics is generally comprised of two divisions:

• Predictive Analytics
• Prescriptive Analytics

Predictive Analytics: What might happen in the future

Predictive Analysis is the third and most critical process of Advanced Analytics. It uses techniques like artificial intelligence, data mining, machine learning, modelling, and statistics to make predictions. Predictive modelling helps businesses like healthcare, marketing, sales, supply chain etc. to optimize operations, improve customer satisfaction, manage budgets, identify new markets, anticipate the impact of external events, develop new products and set business, marketing and pricing strategies.

Prescriptive Analytics: What should be done

Prescriptive analytics is a vital tool used in creating data-driven decisions. optimizing operations, growing sales, managing risks formulating strategies, and reaching organizational goals. It uses statistics and modelling to recommend future actions by applying data to the decision-making process.

Advanced Analytics and Business Intelligence Market Size

The Advanced Analytics market is showing continual progress as enterprises embrace these tools to effectively manage complex business processes. Reportlinker.com predicts that the global Advanced Analytics market size may grow from USD 33.8 billion in 2021 to USD 89.8 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 21.6%.

A similar trend can be noticed in the case of the Business Intelligence market too. To quote Fortune Business Insights, “the Business Intelligence market is set to reach USD 43.03 Billion by 2028 in connection with rapid digitisation and robust demand for data personalisation to foster market development”.

Business Intelligence

Advanced Analytics is all about predicting future strategies, whereas Business Intelligence is focused on past performance, relying on methods such as querying, reporting, and dashboards. It uncovers trends and presents findings through visualization tools. The results show that companies adopt new approaches to increase operational efficiency and improve sales and customer relations through real-time analysis.

Functions of Business Intelligence are listed below:

Data Mining

Data mining is the process of unearthing information and patterns from massive datasets to visualizing in dashboards to generate inferences to assist the decision-making process. By adopting various techniques and procedures, knowledge is extracted to solve business problems to promote sales and marketing.

Process Mining

Powered by Data Mining and Power Analytics, Process Mining extracts insights from the existing data and helps to find the bottlenecks that hinder efficiency and compliance. It ensures a better customer experience, loT process improvement, identifies and analyses supply chain management weak links, optimises procurement and speed-up payment collection.

Complex Event Processing

CEP employs a set of techniques to analyse Big Data for real-time benefits. Opportunities and threats in business operations are identified and monitored to pave the way to success. Companies adopt CEP for fraud prevention and detection, real-time marketing, stock market trading and allied areas.

Business Performance Management

Widely known as Corporate Performance Management (CPM), BPM implies all processes or methodologies that optimise business performance. It also initiates the achievement of business goals like budgeting, planning, and forecasting and helps to improve employee performance. It identifies risks, selection of goals for progressive development, and streamlines financial processes.

Benchmarking

Benchmarking process is evaluating the management practices of one company with its best counterpart. Comparing the organisational processes in relation to the best performances allows companies to evolve by developing plans to improve their tactics.

Top 5 Advanced Analytics Tools

Alteryx: A self-service platform that can help users extract, clean and analyse data through an automated process.

Anaconda: It is an open-source Python and R-focussed platform to analyse and visualise data.

Google Cloud Platform: Known to be one of the enormous machine learning stacks, Google Cloud AI offers many products to analyse and manage data in real-time.

Knime: An open-source software that visualises data flows and helps discover new insights with minimal or no programming.

MS Azure: It is a platform (PaaS) that combines data from various sources, then stores and finally transforms it for different purposes.

Top 5 Business Intelligence Tools

Tableau: Tableau supports multiple data sources to easily analyse and visualise data in handy dashboards.

Power BI: This business analytics tool which can be accessed from anywhere helps in identifying real-time trends and delivering reports via real-time dashboards.

Qlik sense: It is a popular and complete Business Intelligence tool with its unique search and conversational analytics platform that discover new observations using natural language.

Micro strategy: It offers high speed and powerful dashboarding, cloud solutions and hyper-intelligence that can be accessed from a laptop or mobile.

IBM Cognos Analytics: Designed to discover even hidden patterns, Cognos Analytics interprets and presents data in a visualised pattern.

Conclusion

Business Intelligence and Advanced Analytics go hand in hand, from assisting business operations to improving customer satisfaction. Yet they are distinct from each other in their own ways. The amalgamation of these two technologies – Advanced Analytics and BI – improves the efficiency of business operations, delivering predictions based on historical and present data and enhancing performance in sales, maintenance, and customer satisfaction.

The Principles of Data Ethics

And there are five of these principles:

1. Ownership: The individual, himself/ herself/ themself, possesses the ownership of the data related to the person. A firm cannot take that data without the consent of the person lest it be deemed stealing.
2. Transparency: The individual, aka data subject, has the right to know how a particular enterprise intends to collect, store and utilise the data concerned with the person.
3. Privacy: Any bit of Personally Identifiable Information (PII) should not be made publicly available unless otherwise consented to. This includes the name, address, phone number etc.
4. Intention: If the firm is collecting data on the individuals to fulfill unstated malicious intentions, it goes against the spirit of ethics.
5. Outcome: If the collected data, despite the right intentions, come to have an unwanted outcome vis-a-vis the owner of the data, thanks to an algorithmic bias or any other reason, then the data ethics stand violated.

Characteristics of Data Ethics

Largely there are four characteristics that portray data ethics.

1. Vouching for and ensuring data security and protecting customer info: When you handle customer data, as an enterprise, you are bound to protect it, prevent breaches, and ensure data never gets compromised. This is easier said than done. IBM India, in a report, outlines that “data breach average cost increased 2.6% from USD 4.24 million in 2021 to USD 4.35 million in 2022.”
2. Offering clear benefits: It is a kind of social contract clause. You give your consumers greater speed, convenience, value and savings, and they (users, patients, clients, employees, customers and partners) will not be hesitant to part with their data as long as they are guaranteed and followed on the guarantee of data in safe hands not prone to misuse.
3. Provision for consumer agency: Look at this scenario from a McKinsey report: “If a customer receives an offer and says, ‘I think I got this because of how you’re using my data, and that makes me uncomfortable. I don’t think I ever agreed to this,’ another company might say, ‘On page 41, down in the footnote in the four-point font, you did actually agree to this.’ Here, the customer has no agency. Worse than that, he feels he has been duped by the company. Game over! Remember, your reputation as an enterprise and the trust that you painstakingly cultivated over the years with customers can vanish in as much time as it takes for the customer to hit the post button on social media.
4. Doing what you promise: The company should do what it has promised it will do or risk credibility and reputation.

In short, companies that adhere to the principles of fairness, privacy, transparency, and accountability in data matters can earn and retain the trust of their customers or clients. Trust is one power of attorney. It empowers a firm to not only ensure better customer service and experience by exercising the power of data it has been granted but also preserve and enhance its reputation.

Regulations and Data Ethics

Regulatory requirements and ethical obligations are mutually related and complementing. The European Union’s General Data Protection Regulation (GDPR) went into effect (only) in May 2018. But the Internet and data collection using the Internet predate it. Does it mean that companies could have done whatever they wanted to do with data prior to GDPR? Negative.

Ethics is your enterprise’s shadow. It is born with it as its twin. Regulation or law is the caretaker that comes afterwards.

“The bar here is not regulation. The bar here is setting an expectation with consumers and then meeting that expectation—and doing it in a way that’s additive to your brand,” an expert noted.

No wonder you are obliged to build company-specific data usage rules rather than await the regulators and legislators to chip in with guidelines and laws which could be too late or sometimes too little. Ascertain what are the no-go areas; areas where you cannot take the data to.

Once it is done, it is important that you communicate the data values internally and externally so that everyone is on the same page. You also need to set up an agency (e.g. Data Ethics Board) and institutionalise and propagate the values that you designed. C-suite should also be made a part of this ethics board or should be kept posted on the developments in the board.

• List the unused data sources: Data sources imported in a workbook but not used are highlighted by the new feature. The developer can remove these data sources from the data source list to make the workbook faster.
• List of unused fields or data columns: Just like the data sources, workbook optimizer also highlights the data columns not used across the workbook. Removing these at the data source level can help improve the overall performance of the workbook.
• List of sheets not used in the dashboard: It is a common practise that developers tend to create sheets not used in the final dashboard. This creates unnecessary clutter and makes the dashboard slower. The workbook optimiser feature gives a list of such sheets which the user can delete to optimise the performance of the workbook further.
• Highlights lengthy calculations: The feature provides a list of calculations which are too complex and in turn reduce the performance of the dashboard. Simplifying a few of these can improve performance to a great extent.

• Get a list of all the parameters in one place rather than finding them in the flow. One can delete these parameters directly from the parameter window rather than to find it in the flow first.
• Include parameter names in exported output files.
• Include parameters in SQL scripts that you run before or after writing the flow output to a database. Include parameters in worksheet names when writing the flow output to Microsoft Excel.

• 1. Improvements in Esri Data Connector
• 2. Addition of new Accelerators
• 3. Added connectors to connect to more data sources