Tableau User Group: One Unique Network and a Force Multiplier

Why Encryption is Important

Encryption is a security technique that converts data into a format that is unreadable by unauthorised individuals. It is particularly crucial when it comes to protecting sensitive information such as personal data, bank records, and trade secrets. By encrypting data, even if an attacker accesses it, they cannot read it without the correct decryption key.

AWS provides various encryption options to protect data:

1. Server-side Encryption
2. Client-side Encryption
3. Key Management

1. Server-Side Encryption

Data at rest can be encrypted in AWS by using server-side encryption. Server-side encryption is available for AWS services, including Amazon S3, Amazon EBS, Amazon RDS, and Amazon Redshift.

When you utilise server-side encryption, AWS encrypts the data before putting it on a disc. The security of your information is guaranteed because AWS also manages the encryption keys required to encrypt and decrypt data.

2. Client-side Encryption

Data can be encrypted on the client side before being uploaded to AWS. Client-side encryption adds a layer of security by allowing you to manage the encryption keys used to encrypt and decrypt your data.

Client-side encryption is available for AWS services, including Amazon S3, Amazon EBS, and Amazon RDS. Client-side encryption requires additional administration and security measures because it forces users to control the encryption keys directly.

3. Key Management

Key management is the process of generating, storing, and controlling encryption keys. AWS provides critical management services, including AWS CloudHSM and Key Management Service (KMS).

You can easily create and manage the encryption keys to secure data using AWS Key Management Service (KMS), a managed service. Some AWS services, such as Amazon S3, Amazon EBS, and Amazon RDS, are compatible with AWS KMS.

A hardware security module (HSM) called AWS CloudHSM offers secure key management and storage. AWS services, including Amazon S3, Amazon EBS, and Amazon RDS, can be used with AWS CloudHSM.

Best Practices for Protecting Data in AWS

Use these best measures to protect your data in AWS:

1. Encrypt sensitive data: Use either server-side or client-side encryption to encrypt all sensitive data. Robust encryption methods like Advanced Encryption Standard (AES) should exist with 256-bit keys. The Amazon Web Services (AWS) KMS service can generate and manage encryption keys.
2. Utilise AWS CloudHSM: For other key management and security, use AWS CloudHSM.
3. Set up multi-factor authentication: Multi-factor authentication adds security to AWS accounts and services (MFA).

Conclusion

Amazon Web Services (AWS) is a comprehensive cloud computing platform that enables millions of customers worldwide to deploy and scale their services on the cloud while enjoying cost savings upfront. Data security is a critical concern for any organisation, and AWS provides several services to help address this issue. Encryption plays a vital role in data protection, and it is essential to follow best practices to safeguard the security and safety of data on AWS.

Beinex is an AWS consulting partner, and we empower customers to host their BI solutions and much more on the cloud. Our cloud migration experts bring in best-in-class stability and reliability by understanding your business strategy and working closely with you to deploy AWS infrastructure as a service.

What is the Tableau Blueprint Assessment?

The Tableau Blueprint Assessment is a powerful tool that evaluates your organisation's data practices, culture, and technology. It provides a clear picture of where you stand and offers actionable, personalised recommendations to help you advance your data journey. This assessment is vital for driving results through analytics by scaling the use of data and initiating cultural changes.

Key Components of the Blueprint Assessment

1. Blueprint Tracks: Adopt and evolve processes and best practices across four key areas:
• Agility • Proficiency • Community • Governance
2. Data Culture: Foster behaviors and beliefs that empower everyone in your organisation to create business value.
3. Personalised Recommendations: Tailored to your organisation's level and responsibilities spanning business and technical domains.

How Tableau Blueprint Helps You

1. Establishes Your Baseline: Measure where you are in your data journey compared to other data-leading organisations.
2. Tracks Your Progress: Revisit and update your results to see how you advance.
3. Accelerates Your Transformation: Receive actionable recommendations and examples of best practices based on your role and responsibilities.

The Assessment Process

1. Assessment: You answer questions about your organisation's data practices, culture, and technology.
2. Evaluation: The assessment analyses your responses and generates a maturity score across different dimensions of data management.
3. Recommendations: You receive tailored recommendations for improving your data strategy and implementation based on your assessment results.

Benefits of Using the Tableau Blueprint Assessment

1. Identify Strengths and Weaknesses: Understand your organisation's current data capabilities.
2. Prioritise Initiatives: Focus on areas with the highest potential impact.
3. Align Stakeholders: Create a shared vision for data-driven transformation.
4. Access Best Practices: Make the most of Tableau's expertise and industry insights.

Key Areas Covered in the Assessment

• Data Culture • Data Literacy • Data Governance • Data Management • Analytics and Business Intelligence

Blueprint Tracks and Participants

Each Blueprint track includes questions related to capabilities, commitment, and behaviors & beliefs: • Capabilities: 3-5 questions on processes and best practices. • Commitment: 5 questions on executive sponsorship, organizational structure, business value, and investment. • Behaviors & Beliefs: 15 questions on characteristics fostering a successful Data Culture.

Who Should Participate?

• Agility:

1. Capabilities: Tableau Server/Cloud Administrator
2. Commitment: Platform Manager

• Proficiency:

1. Capabilities: Data Visualization & Analytics Trainer, Tableau Champions
2. Commitment: Analytics Lead, Head of Learning & Development

• Community:

1. Capabilities: Tableau User Group Leader
2. Commitment: Tableau User Group Leader, Analytics Lead

• Governance:

1. Capabilities: Data Steward, Tableau Site/Project Administrator
2. Commitment: Chief Data Officer, Governance Council Member

Participants typically include mid-level leaders, front-line managers, individual contributors, executive leaders, and C-suite executives.

Next Steps: Completing the Tableau Blueprint Assessment

1. Identify Stakeholders: Gather a broad set of participants to gain a comprehensive view of your organisation.
2. Host a Kick-off Call: Discuss the assessment and outline expectations with all participants.
3. Complete the Assessment: Set a due date; each assessment will take no more than 20 minutes to complete.
4. Debrief: Host a meeting with all stakeholders to discuss results, recommendations, and next steps.

By following the Tableau Blueprint and leveraging the assessment, your organization can build a robust data culture, enhance data literacy, and implement effective data governance and management practices. Get ready to transform your organization into a data-driven powerhouse.

Top Five Benefits of AWS GRC Solutions

Implementing AWS’s GRC solutions offers several advantages that go beyond compliance. Here are the top benefits: • Data-Driven Decision Making: Real-time monitoring and analytics enable organizations to make informed decisions that align with both strategic goals and compliance objectives. • Fostering Responsible Operations: By promoting a culture of governance and ethical practices, AWS helps organizations operate responsibly and build trust. • Advanced Security Measures: Features like encryption, identity management, and continuous threat detection provide robust protection for sensitive data. • Scalability and Flexibility: AWS solutions scale with your business, ensuring that governance and compliance measures grow alongside your operations. • Cost-Effective Operations: AWS’s pay-as-you-go model allows organizations to optimize their IT budgets while maintaining governance and compliance standards.

AWS and GRC Tools

Amazon Web Services (AWS) provides a comprehensive set of GRC tools and practices that can be integrated into the Governance, Risk Management, and Compliance (GRC) framework that empower businesses to effectively manage their data while adhering to industry standards and regulations. Below are some examples of AWS and GRC (Governance, Risk, and Compliance) tools and practices:

Governance: Establishing a Solid Framework

In the AWS ecosystem, governance refers to setting up policies, guidelines, and processes to ensure effective data and resource management. This framework supports business objectives while promoting ethical practices, transparency, and adherence to regulatory requirements. AWS provides several GRC tools and practices that centralize governance and enhance control over accounts, resources, and configurations. • AWS Organizations: This tool helps organizations manage multiple AWS accounts in one place, allowing for the easy implementation and enforcement of policies across the enterprise. Through Service Control Policies (SCPs), organizations can control permissions and ensure only authorized actions occur. • AWS Config: AWS Config is essential for governance as it tracks changes in AWS resource configurations. By providing detailed insights into the state and relationships of these resources over time, AWS Config ensures compliance with internal and external standards. • AWS Service Catalog: The AWS Service Catalog allows organizations to maintain oversight of their IT environment by managing catalogs of approved services. This guarantees that only pre-approved and compliant software, databases, and configurations are deployed. • AWS Control Tower: AWS Control Tower simplifies setting up and managing a secure, multi-account AWS environment. It automates governance best practices and continuously monitors compliance with pre-configured guardrails.

Risk Management: Safeguarding Against Threats

Identifying and managing risks is crucial in today's digital landscape. AWS offers a range of services to help organizations monitor their infrastructure, detect potential vulnerabilities, and respond to security threats swiftly. • AWS CloudTrail: CloudTrail logs and monitors API activity within AWS, allowing organizations to trace user actions and conduct investigations after security incidents. It’s also useful for forensic analysis to determine the cause of issues. • AWS Security Hub: As a centralized security dashboard, AWS Security Hub aggregates findings from multiple AWS services, helping businesses streamline incident response and maintain compliance. • Amazon GuardDuty: GuardDuty is a security service that detects suspicious activities and unauthorized behavior in AWS accounts. By leveraging machine learning and threat intelligence, it helps organizations preemptively address potential risks. • AWS Config Rules: These customizable rules automatically check resource configurations for compliance. If a resource deviates from the expected settings, alerts are triggered, enabling proactive issue resolution.

Compliance: Ensuring Adherence to Regulations

Compliance is vital for any organization handling sensitive data. AWS simplifies the process with a variety of tools to help organizations meet regulatory requirements and reduce audit burdens. • AWS Artifact: AWS Artifact offers on-demand access to important compliance documents, such as SOC reports and certifications like ISO and PCI DSS. This is especially helpful during audits, providing immediate access to evidence of AWS's adherence to standards. • AWS Shield & AWS Web Application Firewall (WAF): These services protect against DDoS attacks and unauthorized access attempts, ensuring web application availability and data integrity. Shield and WAF work together to filter out malicious traffic and ensure the security of incoming requests. • AWS Key Management Service (KMS) & AWS Certificate Manager (ACM): Data encryption is critical for compliance, and AWS KMS helps manage encryption keys securely. ACM automates the deployment of SSL/TLS certificates, protecting data both in transit and at rest. • AWS Audit Manager: AWS Audit Manager automates evidence collection for audits, continuously assessing your environment against industry standards. This reduces manual effort and ensures that organizations remain consistently compliant. AWS’s robust GRC framework empowers organizations to effectively manage data, mitigate risks, and ensure regulatory compliance. Leveraging AWS’s advanced tools not only supports meeting industry standards but also fosters innovation, resilience, and future-readiness within businesses.

Beinex: AWS Partner for the Middle East

Beinex is an AWS consulting partner, and we empower customers with AWS managed services to host their BI solutions and much more on the cloud. Our cloud migration experts bring in best-in-class stability and reliability by understanding your business strategy and working closely with you to deploy AWS infrastructure as a service. Connect with Us for a Free Demo Interested in our services? Try AWS for free: https://beinex.com/beinex-amazon-web-services/

Tableau has been one of the most popular data visualization and analytics tools among the business users in the last decade. With the new features it is even simpler to see and understand data. It is evident that Tableau is made with the intention of appealing to everyone, even those with very limited technical know-how. As always, the new version of Tableau is also packed with a punch. There are over 25 new features over the Desktop, Online, Prep and Mobile versions of the tool. Here are a few of them, that would significantly change the way you use this incredible platform. I have been using this tool since the release on 6th May 2020. After a week of using it, I am convinced that the changes are significant and extremely useful. This new version seems a lot smoother (yes, that is the feeling you get when you use it), even compared to 2020.1, which was released last quarter. I will be focussing on some of the changes in the first blog, that would give you an overview and help you get started with this. 1. Relationships As a trainer on Data Analytics for the last three years, I have experienced one struggle. It is about explaining the concepts of ‘Joins’ to business users. They find it confusing to know when to use ‘left join’ and when to use ‘full join’. (IT users and students had very limited issues since they have learned these concepts). Challenges like duplicate / repeating records in one of the tables (one to many mapping) is definitely hard to tackle unless you master the concepts and other techniques. However, in Tableau 2020.2, it uses ‘Relationships’ which is a much simpler and easier concept to understand, and Tableau does the heavy lifting if you are unsure In this version, you can create logical relationship with data, visually. Relationship creates aggregations when you build the visualizations, rather than joining them in the database. This means that you can forget worrying about having to keep the data in the same level of details and the complications that would arise if it is not. For those who are familiar with the tool, the visual difference itself is quite significant. As soon as you drag and drop the second and subsequent tables, a relationship line (‘Noodle’ is what Tableau named these lines) appears and makes it easy to define the connection. Once you add the table, a pop-up box suggests the best connection, where you can define further details (Cardinality and Referential Integrity) if needed. You can also view each of the tables independently even after defining the relationship. All you need to do, is just click on the table. You can also use the existing concepts of Union and Joins as well. Below is a simple example using Sample Superstore data. 2. Metrics Metrics is a concept that would appeal to the higher management and executives. This is an option where you can track all metrices of your interest in one place, despite of it being included in multiple Tableau workbooks. Instead of creating a ‘Master Workbook’ with all the metrics, which involved development and maintenance effort, we can now do it with a simple click. It will add the Metrics or KPIs to the main Project folder itself. In addition, you can also see the trend of that particular metric over the period when the data refreshes. In the example below, I have one Project in Tableau Online, which has got multiple dashboards catering to different business areas. I am adding two metrics: the number of male employees in the organization, and the YTD Sales. Since the data is not refreshed, the timeline will be empty. Just check out how easy it is to add the Metrics to monitor it continuously and effectively. 3. Set Controls and Set Action Updates While this might be described as a new feature, it, in fact, opens a whole new set of opportunities to interact with your visualizations. If I try to describe set Controls in Tableau 2020.2, it can be simplified as an option in which we can include or exclude elements in a set in a simple drop-down (similar to ‘Filters’). The addition or deletion or new values in a set can significantly change the way we see the data. This means that the end user can perform a variety of analysis in the front end. Check out the video below. Set actions also has got two new selection modes as well in the new version. Tableau 2020.2. Instead of only assigning the set values, Set Action can now add or remove values incrementally, by interacting with the marks. Zen Masters ‘The Flerlage Twins’ have a blog that explains all the features in details about this new set action option. You can check it out.: 4. Other Changes No Dimensions or Measures: One of the noticeable differences compared to the previous version, is the absence of sections for Dimensions and Measures. While there is separation line, it is less distracting than the previous versions. It is not only the Dimensions and Measure that got combined, but also the section for Sets. In this version, when you add a Set it will be added as another field in the table, just like a calculated field. This also makes complete sense, since the Sets already have a separate icon to denote them, and it can be clearly understood before using it for any analysis. However, there is a separate section for Parameters. Always on Search Bar: Also, the Search bar is now always visible and cannot be hidden, unlike the previous version. I prefer this option since I almost always enable the search and never hides it afterwards. The Search bar sits comfortably in the space that is created when the titles for Dimensions and Measures are removed. In addition, when you type a field name after selecting any field, it automatically goes to that field despite of whether it is Measure or a Dimension. This is similar to us typing a folder or filename to find it in a Windows Folder Explorer. No more ‘Number of Records’: Another difference is the absence of ‘Number of Records’ field. This is now replaced with a non-editable and non-removable field: ‘Tablename (Count)’. Since the data is defined by relationship and not joined, there will be multiple such fields if you use multiple data sources. Similarly, when we choose ‘View Data’, there will be multiple tabs based on the number of data sources we use. I have tried to show these in the image below. 5. Explain Data and Ask Data Improvements There are significant improvements in these features in every version and this time is no different. Even with all the AI capabilities, there would be times when we want to take control. Explain Data in the new version gives you that extra control that was missing in the earlier version. Authors can now choose which fields to be included in modelling Explain data, giving you the option to input your business logic to it. Explain data also allows you analyse more than just one outlier in the latest version. However, this option seems to be missing for relational databases. When it comes to Ask Data, you can now provide custom suggestions based on data roles. In addition, the synonyms applied for one field can be published to use across data sources. It also supports scripted data sources in the new version and has some improvements on enterprise controls. As mentioned at the beginning, there are several other features in Tableau 2020.2. It would be extremely difficult to include all those in just one post. There are other changes like Recommendations on Mobile, Manual sorting of Favourites, publishing directly from the browser without having to open the dashboard on Tableau Desktop etc. and so on. I hope you got an overview to some of the new features and want to explore more. Let us know your thoughts and how these features were beneficial to you. As mentioned at the beginning, there are several other features in Tableau 2020.2. It would be extremely difficult to include all those in just one post. There are other changes like Recommendations on Mobile, Manual sorting of Favourites, publishing directly from the browser without having to open the dashboard on Tableau Desktop etc. and so on. I hope you got an overview to some of the new features and want to explore more. Let us know your thoughts and how these features were beneficial to you.

Key Trends in GenAI: Be Always in the Know

The latest GenAI trends can take your business by storm, bringing significant transformations, improvements, and competitive advantages powerfully as follows:

1. Hyper-personalized marketing: Marketing That Knows You Better

Imagine a world where every ad you see feels made just for you. Generative AI is making that happen by analyzing tons of data to understand your likes and dislikes. Businesses can now tailor their campaigns so perfectly that it’s almost spooky—in a good way! For example, AI can track your browsing history and suggest exactly the product you didn’t know you needed. It’s like having a personal shopper in your pocket. Plus, in education, platforms use AI to adapt lessons based on how well students do, making learning more effective and fun.

2. AI-driven automation: Getting Stuff Done Automatically

Let’s face it: no one likes spending hours on repetitive tasks. That’s where generative AI comes in. By 2025, it’s expected to automate up to 30% of business operations. Think about supply chain processes, scheduling, or managing employee requests—AI can handle everything. For instance, companies are already using AI to speed up inventory management or even predict what products will be in demand. And customer service? AI-powered bots can answer questions faster and better than ever.

3. Conversational AI: Chatbots That Understand You

If you’ve ever had to deal with a clunky chatbot, you know how frustrating it can be. But conversational AI is leveling up. By 2028, virtual assistants and chatbots will feel more like talking to a helpful human than a robot. They’ll be able to understand complex questions, respond in natural language, and even handle customer complaints like pros. Industries like healthcare and banking are already using this to make their customer service faster and more efficient. No more waiting on hold for hours!

4. Multi-Modal GenAI: AI That Gets All the Details

Generative AI is becoming more intelligent by combining different types of data—text, images, video, and even sound. This is called multi-modal AI, and it’s a big deal. Why? Because it can look at all these inputs together to give a complete picture. For example, retail companies use this technology to analyze how customers behave online and in-store. It helps them precisely recommend what customers want, whether a new outfit or a better grocery deal.

5. AI & Healthcare: A Big Boost for Healthcare

Generative AI is saving lives. Seriously. It’s helping doctors create personalized treatment plans by analyzing patient data, medical history, and test results. AI is also speeding up research, making discovering new drugs and treatments easier. More than 75% of healthcare companies are exploring AI. This means faster diagnoses, fewer errors, and more time for doctors to focus on their patients.

6. AI and Cybersecurity: Fighting Cybercrime Like a Pro

With the rise of digital threats, cybersecurity has become a top priority. Generative AI is stepping in to help by detecting suspicious activity before it becomes a full-blown attack. By 2027, AI-powered systems will drastically reduce false alarms, making it easier for companies to stay safe.

7. Ethics and Regulation: Keeping AI Ethical

As AI gets smarter, questions about how to use it responsibly are growing louder. Governments and companies are working to create rules that ensure AI is fair, safe, and doesn’t harm anyone. For example, the EU focuses on making AI ethical and transparent, while the U.S. takes a more flexible approach to encourage innovation. If you’re a business owner, now’s the time to ensure your AI practices are legal and ethical.

8. Decentralized AI: Better Privacy

What if you could use AI without worrying about your data being misused? That’s what decentralized AI aims to do. Using blockchain technology keeps your data private and secure, giving you more control over its use. This is especially important in sensitive industries like healthcare and finance.

9. GenAI and Business: Bringing Big Wins

In the business world, the true potential of generative AI lies in fine-tuning models to meet specific needs. By 2025, enterprises will hold the reins of AI, leveraging it to drive innovation. Success won't come from simply having vast amounts of data. It will hinge on adapting AI models to work seamlessly with that data. Customized multimodal LLM fine-tuning and evaluation datasets customized to specific use cases enable precise model training. This empowers businesses to unlock the full value of their data and maintain a competitive edge with AI.

10. Open-source models: Pushing Boundaries

This year marks a breakthrough for open-source AI models like Meta’s Llama, Mistral, and Google’s Gemma, offering affordability and accessibility that empower developers and small businesses to innovate. Open-source models like "Llama 3" enable companies to integrate AI seamlessly, transforming businesses of all sizes into AI-driven operations. Open-source fuels innovation and adoption, while closed-source models push AI's boundaries—both are vital for progress.

11. Human-in-the-Loop (HITL): Trend

Human-in-the-loop (HITL) is a key trend, emphasizing the integration of human feedback into Generative AI. This ensures that AI models align with ethical standards, cultural nuances, and real-world needs. HITL improves AI accuracy and fosters collaboration between human expertise and AI. By using HITL, organizations can harness the power of AI while maintaining control over outcomes. Our research also highlights how LLMs can generate inaccurate results without proper human oversight.

12. Agentic AI: Latest Addition

Agentic AI just popped up in mid-2024, the hottest topic for 2025. What's so special about it? This new kind of AI can operate independently, making decisions and acting without needing us to guide it at every step. This is quite different from older AI, which only did what we told it to. These AI agents are especially useful in customer service, where they can handle tasks more efficiently, saving time and increasing productivity, or in finance, where they quickly analyze data and offer recommendations.

13. AI in the Creative Industry: Taking the Lead

Generative AI isn’t just about data and numbers—it’s getting creative too! It’s used to design clothes, create digital art, and even compose music. Imagine a fashion brand using AI to develop the next big trend or a filmmaker creating a blockbuster script with AI’s help. It’s opening up endless media, entertainment, and advertising possibilities.

14. AI in Gaming: Immersive than Ever

If you’re a gamer, get ready for some serious fun. Generative AI creates immersive games by creating dynamic characters, realistic environments, and engaging storylines. Imagine playing a game where the plot changes based on your decisions—AI makes that possible.

Wrapping It Up: The AI Revolution Is Here

Generative AI is more than a tool; it’s a game-changer. From personalized shopping experiences to groundbreaking medical discoveries, it’s transforming every part of our lives. The best part? We’re just getting started. As businesses and individuals, now’s the time to embrace this exciting technology. Whether you’re an entrepreneur, a tech enthusiast, or just someone curious about the future, there’s much to look forward to. So, what are you waiting for? The AI revolution isn’t coming; it’s already here. Let’s make the most of it!