The Second TUG Meetup in Cairo: The Next Step into the Realm of Tableau Users

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How AI Decision-Making is Improving Enterprise Outcomes

Looking to up your game in Business Intelligence and Data Visualization? Want to explore the endless possibilities of Tableau, showcase your work, and get valuable feedback from like-minded peers? Then TUG Meetup is the right event.

The Second TUG Cairo Meetup

Beinex has sponsored the second Tableau User Group Meetup in Cairo, and we are glad to initiate a thriving community that promotes learning, growth, and networking. TUG provides the perfect platform to connect with others, exchange ideas, and gain inspiration whether you're a beginner or an expert in Tableau. At the second TUG Meetup Cairo, the participants got the opportunity to showcase their work, receive constructive feedback, and be part of a community that shares their passion for data visualisation.

Date: March 11, 2023
Venue: MQR, The GrEEK Campus Downtown, Cairo Governorate 11513
Time: 2 PM to 5 PM GST.
We had a great discussion with the following eminent speakers on the topics enlisted below:

#	Speakers	Designation	Topics
1	Khaled Hoza	Data Analyst Team Lead, Fawry	Analyse the performance of your customer retention strategy
2	Martina Ghali	Senior CRM Specialist, Cartona	Overview of digital marketing and get it visualised in Tableau
3	Ahmed Ismail	NLP Engineer, Agolo	Visualise your text analytics in numerous ways

Abdelaziz Mahjoub, Data Analytics Lead Consultant, Beinex was the leader of the TUG Cairo Meetup. He is the first and only Tableau Public Ambassador in Egypt and MENA Region, Tableau public featured author, 1x #VOTD, and Tableau certified associate with practical and academic knowledge of Essential Design Principles techniques.

Initiating a New Tribe that Helps to Grow

[sc name="quote" quote="“Since my early days in the field, I struggled to get help on how to start, a lot. I know how hard it’s to fully understand a certain technology or a tool to a mastery level without proper guidance and mentoring. Here in Cairo TUG, I try my best to help other people not to find themselves in my position back then. That’s why I started Cairo TUG, to build a strong community that everyone can rely on to get help and find the proper guidance”" author="Abdelaziz Mahjoub, Lead Consultant, Analytics at Beinex Consulting,
He is the master brain behind the Cairo TUG."][/sc]

The Second TUG Meetup in Cairo: The Next Step into the Realm of Tableau Users
“Since my early days in the field, I struggled to get help on how to start, a lot. I know how hard it’s to fully understand a certain technology or a tool to a mastery level without proper guidance and mentoring. Here in Cairo TUG, I try my best to help other people not to find themselves in my position back then. That’s why I started Cairo TUG, to build a strong community that everyone can rely on to get help and find the proper guidance”

Data Ethics: Principles, Characteristics and Regulatory Aspects

The Principles of Data Ethics

And there are five of these principles:

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.
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.
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.
Intention: If the firm is collecting data on the individuals to fulfill unstated malicious intentions, it goes against the spirit of ethics.
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.

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.”
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.
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.
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.

Let the force be with you: Data residency and Hyperforce

After two very long masked years, the world has slowly started to breathe, again! With lockdowns on and work taking place from the very room you had slept a couple of hours back -- the human universe has been phenomenally re-engineered by a microscopic organism. Your geographical location has been made immaterial in the digital world. But the same cannot be said about data, and this may sound paradoxical and ironic. For instance, an MNC’s location of the data now matters more than ever before. With a major chunk of data of many entities, especially government ones, on the public cloud, the airing of concerns related to data security, data sovereignty, data localisation/ data residency is growing louder in decibel terms.

This is where Hyperforce comes in.

Hyperforce is how Salesforce has reimagined its platform. It is now horizontally scalable, and through tie-ups with major cloud providers, the scalability has grown by leaps and bounds. Imagine you are a B2B company with 10,000 customers or a B2C company with tens of millions of customers: Hyperforce lets you scale up your capabilities and provides you with a single source of truth. But what if you are a multi-geographic business conglomerate in a heavily regulated industry like finance or health? How will you comply with data sovereignty, data localisation/ data residency requirements? Hyperforce’s collaboration with public cloud companies ensures that the data can be located at any specified place in the world, adhering to the local rules of data governance and storage locations. “Choose the location where your data will be stored to comply with regulations specific to your company, region, or industry — even in highly regulated industries like the public sector,” the store-data-locally-keep-it-compliant-globally mantra tells. Other features Hyperscalable: Hyperforce also enables you to scale the infrastructure as per the needs of the business by letting you access extra computing capacity as and when required. You can employ resources in the public cloud rather quickly. Yes, it is your decision whether to scale up or not, and the elasticity can be dictated by the nature of your requirements. Hypersecure: Also, trust is built-in, which puts security at the forefront of the architecture. Data privacy and security are sacrosanct. This leaves you with enough room to focus on innovation. Hypercompatible: And most important of all, backward compatibility ensures that all the extant Salesforce apps, customisations and integrations will continue to work on Hyperforce regardless of cloud. In the physical world, your geographical location assumes importance. But in the digital world, it is the location of the data that matters. Hyperforce, by virtue of its collaboration with major players in the cloud domain, ensures data residency requirements are adhered to when and where needed. The architecture is hyper-scalable, secure, and comes with backward compatibility. Hyperforce is soon to be launched in the UAE, and Beinex, a Salesforce partner, is all set to carry out implementation and consulting of and for Hyperforce.

Governing Agentic AI: How Organizations Can Balance Autonomy, Risk, and Accountability

Agentic AI is redirecting AI to autonomous systems that can plan, decide, and execute tasks independently. These AI agents can manage workflows, interact with software systems, and trigger actions without continuous human input. While this autonomy promises efficiency and scalability, it also introduces new governance challenges.

Research shows that 86% of enterprises expect higher risk levels with agentic AI, yet only 2% of organizations currently meet responsible AI standards. This gap highlights a critical reality: organizations must adopt a structured agentic AI governance framework to balance autonomy with accountability.

Benefits of Advanced Analytics: From its Impact on Company Culture to Business Financials

Advanced Analytics aids in the resolution of complicated business challenges, as well as the improvement of operational efficiency, investment decisions, and customer experiences. It goes one step ahead of business intelligence by employing sophisticated modelling approaches to forecast future occurrences and find trends/patterns that would otherwise go undetected. Let’s get into the benefits of Advanced Analytics in detail:

Benefits of Advanced Analytics:

Transformation of Company Culture

Organisations must transition to a data-driven culture that questions assumptions, addresses crucial topics, and rewards everyone who can provide and analyse value-added data. Companies reap a bunch of benefits by adopting a data-driven culture. The prevalence of such a culture gives employees the talents and skills to analyse data and develop valuable insights, resulting in more accurate decision-making. When a data-driven culture is established, employees can actively seek out more relevant data to fine-tune goals and objectives.

Predicting the Future

Using Advanced Analytics, organisations can assess market circumstances faster and respond to changes faster than their competitors, giving them a considerable edge. Big Data analytics are frequently leveraged by financial services organisations looking to mine, for instance, massive amounts of stock market data to identify and capitalise off of previously unknown trends. Public health organisations are also increasingly leveraging vast population health data to develop better policies, treatment and healthcare practices.

Faster Decision-making

Data analytics helps businesses make better decisions and reduce financial losses. Predictive analytics can forecast what will happen due to business changes, while prescriptive analytics can recommend how the company should respond. Executives may move more rapidly when they have high-accuracy projections, knowing that their business decisions will produce the intended effects and that favourable outcomes can be replicated.

Day-to-day decisions made by retail, manufacturing, media, and healthcare (to name a few) are influenced by the accuracy of insights provided by Advanced Analytics capabilities. It aids in the creation of specifically targeted ads, leads to effective inventory management, spotting quality control issues and anticipating fluctuations in labour needs.

Gathering Deeper Insights

Advanced Analytics enables stakeholders to make data-driven decisions that directly affect their strategy by providing a deeper level of actionable knowledge from data, such as customer preferences, market trends, and essential business processes. Actionable data insights obtained after properly analysing data optimise performance and help make informed decisions.

New products or services are launched, and new markets are uncovered to gain new revenue resources. Customer loyalty and satisfaction increase through deep insights earned through data analysis.

Improved Risk Management

Analytics, in general, assists a company in identifying hazards and taking preventive steps.

Employing sophisticated analytics to make more accurate forecasts, Advanced Analytics allows firms to avoid costly and dangerous actions based on faulty projections. Advanced Analytics gives enterprises a holistic view of their business, past, present, and future, allowing them to better identify and manage risk. The improved accuracy of Advanced Analytics predictions can help firms lower the danger of costly blunders.

Different sectors like banking, telecommunications, and government agencies seek help of Advanced Analytics in identifying, assessing and prioritising risks. Timely identification and monitoring of risks using technology make risk management much more accessible.

Anticipating Problems and Opportunities

Companies can use Advanced Analytics to solve problems that traditional BI can't. It can recommend activities that will improve business outcomes based on probability. Advanced Analytics reduces decision-making uncertainties and allows enterprises to take more effective data-driven decisions. Enterprises take much more of insightful decisions without any programming support from data scientists. It also eliminates customer problems before it arises by converting silos of data into insightful information clusters.

Advanced Analytics employs statistical models to uncover potential difficulties with the company's trajectory or find new opportunities, allowing stakeholders to change course rapidly and achieve better results. Thereby enterprises will discover the accrual of a unique competitive advantage and power to uncover previously unseen trends that project them into an influential positions.

Personalising the Customer Experience

Personalised experience has gained momentum, and companies are ready to offer it more and more to their customers: accessing and mapping relevant data pools to identify customers’ needs and expectations and create a unique experience tailored for them. Also, they deploy Advanced Analytics to improve productivity, optimise business operations, ensure customer experience and more. Effective data utilisation continuously improves workforce efficiency, and by tracking customer engagement, companies can offer a seamless experience to the customer.

Customers' data are gathered through various channels, including physical retail, e-commerce, and social media. Businesses can get insights into client behaviour by employing Advanced Analytics to construct complete customer personas from this data, allowing them to give a more personalised experience.

Improving Financial Performance

The financial performance of the companies, irrespective of the sector, improves by making the best out of Advanced Analytics. The sales forecasting accuracy increases, organisational trends are uncovered, and challenges are addressed competitively, highlighting the business growth. With the marketplace becoming exceedingly competitive, making more confident decisions are inevitable using analytics tools.

Thanks to Advanced Analytics, the biggest businesses worldwide are seizing on the opportunity to make the best of Advanced Analytics. Those enterprises that would like to steal the show can manoeuvre the operations to killer effects by adopting analytics. So, it’s time to get ahead of the curve by the intelligent use of big data for advanced solutions, cutting-edge advertising strategies, and targeted marketing campaigns.

Tableau Version 2021.4: Bringing Automation to Data Management

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

Data Management
1. Virtual Connections
2. Centralized Row-Level Security
Tableau Catalog
1. Inherited column descriptions
2. Create flows from Catalog pages
Tableau Prep Builder
1. Tableau Prep Parameters
2. Create Tiles
3. Flow output Subscriptions
Tableau Online
1. Connected Apps
2. Tableau Bridge Multi-Pool
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.