Tableau + AWS: Dashboards Development Using AWS Glue DataBrew

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How AI Decision-Making is Improving Enterprise Outcomes

With AWS Glue DataBrew, we can transform and prepare datasets from Amazon Aurora and other Amazon Relational Database Service (Amazon RDS) databases and upload them into Amazon S3 to visualise the transformed data on a dashboard using Tableau.

Here is how to do it:
With AWS Glue DataBrew, we can:
1. Transform and prepare datasets from:
a. Amazon Simple Storage Service (Amazon S3)
b. Amazon Aurora
c. Amazon Relational Database Service (Amazon RDS) databases
2. Upload them into Amazon S3
3. Visualize the transformed data on a dashboard using Tableau

Method:
1. You can create a JDBC connection for Amazon Redshift and a DataBrew project on the DataBrew console.
2. DataBrew queries data from Amazon Redshift by creating a recipe and performing transformations.
3. The DataBrew job writes the final output to an S3 bucket in Tableau Hyper format.
4. You can now upload the file into Tableau for further visualisation and analysis.

Result: Creation of predictive dashboards on top of the S3 bucket

About AWS Glue DataBrew
AWS Glue DataBrew is a tool for data analysts and scientists that simplifies cleaning and standardising data to prepare it for machine learning and analytics.

Integration of Tableau and AWS services, specifically using AWS Glue DataBrew, can be utilised to develop dynamic dashboards. These tools offer efficient data preparation and visualisation capabilities, enabling users to gain insights quickly from their data. Follow along to learn how to combine the power of Tableau and AWS for your data analytics needs.

Generative AI Trends in 2025: Shaping the Future of Business Success

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!

NEW FEATURES OF TABLEAU 2020.1 (BETA)

Soon after Tableau launched the 2019.4 update, they have released a list of super interesting features as part of their path into 2020.1. Despite it being in Beta stage, we have been able to try out some of these and they do change the way we think about visualizations and the way we interact with them. Let’s go through a sample of the most coveted features, which many of us in the world of BI have probably been dying to have (or at least would be great to have!)

1. Dynamic Parameters

1. This one deserves a whole lot of excitement from the entire Tableau community since parameters are used in just about any viz and the biggest complaint (major pain!) was that if the data gets refreshed, the updated values in the parameter field do not get reflected. A user would have to manually go about refreshing and adding the new fields in the parameter. It was honestly astounding that such a simple thing would be the source of unnecessary emotions soaring. 2. But with the latest update, Tableau has provided. Now it can automatically update its parameters as soon as the data is refreshed and the new values will populate by itself! This saves a ton of time and effort and monitoring headaches for every dashboard created hereon! 3. To us, this would be among the most coveted and REQUIRED updates in this version

2. Viz Animations

In this new day and era, we are used to smooth rendering of just about anything we work on (from an app on our phone to the way an electric car feels on the road). This concept has now been delivered to us by Tableau in their new viz animation capability. Now all our charts can have a smooth flow whenever changed by another filter. This not only enables the user to spot the exact points of change in the chart, but also looks cool beyond measures. On click of an action, we can set up the amount of time it will take for the change to take place in the other charts (and this change is animated smoothly). This beautiful feature can be perfectly explained using an example visualization, rather than any more words. So here goes..

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As you can see, it looks beautiful. This is an exciting time for the creators, since this feature will definitely make the viz functionality immensely more appealing to an end user.

3. Improvements in Explain Data

For those unfamiliar to this feature, explain data is an intelligent tool built in tableau which gives a statistical inference to any singular data point on a chart. It gives us an idea of the why and the general direction of the how of the value. 2020.1 promises to be smarter with Explain Data digging deeper with more refined statistical models in the background. This is a feature which never fails to astonish a new user and Tableau promises to keep improving and building upon this as time goes by.

4. Export the dashboard to formats wanted

This is a simpler feature amidst all the fancy ones, however, may prove to a crucial addition for end user experience. Now we can directly export the dashboard in any format, on click of a button which can take the form of a text or an image and put as part of the dashboard. No more explaining to users to find click the tiny download option on the bottom of the screen and then export, now we can directly do it at the click of a button! We can export to formats like PDF, PowerPoint etc. which is honestly, great.

5. Buffer calculations

Buffer calculation enhances the interactivity when it comes it spatial scenarios. It is a boundary created with respect to any point on the map or location. A buffer calculation should contain three parameters such as location, distance, and a unit of measure like ‘kilometer’, and ‘miles’. Simple use case like, when you wanna know how many restaurants are present near my hotel, say around 1km, the buffer boundary highlights the number of restaurants near a specific location. Here is how the buffer calculation works….

[video width="1296" height="1080" mp4="https://www.beinex.com/wp-content/uploads/Video-2-Buffer-Calculation.mp4"][/video]

So restricting to only the Desktop version of Tableau, we can foresee happier times for all viz lovers. Though these features are just part of the BETA version and may not all be released in the very next update, but these are good to look ahead to.

Best Practices to Accelerate a Smooth Transition from On-Premises to Cloud with Snowflake

9 Key Areas to Focus on During Cloud Migration

1. Data Compression

Efficient data compression conserves bandwidth and speeds up data transfers. Best Practice: Use reliable compression formats like gzip to prepare data for upload. How Snowflake Helps: Snowflake supports ingesting compressed files and automatically compresses uncompressed files during uploads, saving time and resources.

2. Initial Data Uploads

Large-scale data transfers require secure and efficient methodologies. Best Practice: Use tamper-proof, one-time transfer solutions for large datasets. How Snowflake Helps: Snowflake integrates with AWS Snowball, Azure Databox, and Google Transfer Appliance, making massive data migrations seamless and secure.

3. Ongoing Data Uploads

Continuous data ingestion is essential for keeping cloud databases updated. Best Practice: Build pipelines to automate the ingestion of newly generated data. How Snowflake Helps: Tools like Snowpipe, COPY commands, and Snowpipe Streaming support real-time and batch data uploads, ensuring uninterrupted data flow.

4. Data Set Prioritization

Prioritizing critical data minimizes redundancy and ensures efficient migration. Best Practice: Start with "master data sets" and avoid unnecessary duplication. How Snowflake Helps: With user-friendly options like its web interface, Snowflake simplifies the process of structured data migration.

5. Data Lifecycle Management

Managing data retention optimizes storage costs and aligns with compliance requirements. Best Practice: Implement policies to archive or delete obsolete data. How Snowflake Helps: Snowflake’s cost optimization tools and upcoming policy-based features streamline lifecycle management.

6. Data Security and Encryption

Protecting data during and after migration is paramount. Best Practice: Use encryption and private connectivity for secure transfers. How Snowflake Helps: End-to-end encryption, robust key management, and features like Private Link ensure data security throughout its lifecycle.

7. Data Validation

Validating data quality builds trust and ensures accurate analytics. Best Practice: Monitor metrics like null values, duplicates, and data freshness. How Snowflake Helps: Snowflake’s built-in functions detect anomalies and maintain data integrity.

8. Disaster Recovery

Cloud platforms simplify disaster recovery with built-in capabilities. Best Practice: Leverage cloud-native DR features to enhance data resilience. How Snowflake Helps: Snowflake’s Snowgrid technology and features like replication, failover, and time travel ensure business continuity.

9. Managing Multiple Environments

Cloud scalability simplifies managing development, testing, and production environments. Best Practice: Automate environment deployment and resource allocation. How Snowflake Helps: Zero-copy cloning, CI/CD tool integration, and instant resource access streamline environment management.

How Snowflake Transforms Migration Challenges

Snowflake’s cutting-edge tools address common migration challenges, offering: Efficiency: Automated compression, seamless data uploads, and scalable pipelines. Security: Robust encryption and compliance-friendly features. Flexibility: Support for diverse data ingestion methods and environment setups.

Defining Clear Objectives for Migration:

1. Primary Drivers of Migration for an Organization: Common drivers include: • Reducing operational costs. • Enhancing scalability to manage growing datasets and user demands. • Enabling advanced analytics capabilities to improve decision-making. • Improving system performance for faster query execution. • Lowering maintenance overhead by moving to a cloud-native platform. 2. Critical Migration Assessment: Before committing to migration, organizations should evaluate whether the benefits outweigh the risks and costs. This involves: • Assessing alignment with strategic goals. • Identifying potential technical challenges or limitations. • Determining readiness for organizational change and adoption.

Assessment Before Migration:

1. Evaluate Current Architecture, Data Volume, and Workload: Conduct a thorough audit of the existing data infrastructure, analyzing data volume, complexity, and system performance to determine migration readiness. 2. Identify All Data Sources, Pipeline/ETL Processes: Create a comprehensive inventory of data sources and existing ETL pipelines to understand the flow and transformations applied to data. 3. Map Dependencies Between Datasets and BI/Analytics Applications: Identify interdependencies between datasets, applications, and users to ensure no analytics or reporting post-migration disruption.

Utilize Snowflake's Features:

1. Data Sharing: Enable seamless live data sharing between internal teams and external partners without duplication. 2. Scalability: Automatically scale resources up or down based on workload demand, ensuring cost-effective performance. 3. Time Travel: Leverage historical data snapshots for recovery, audits, or analytics within a specified retention period. 4. Built-in Security: Utilize Snowflake’s enterprise-grade security features like end-to-end encryption and multi-factor authentication. 5. Streamlit and Cortex Functions: These features can be harnessed to build custom applications and natively perform advanced machine-learning operations on the Snowflake platform.

Data Governance:

1. Establish Policies, Access Control, and Data Classification: Snowflake’s role-based access control (RBAC) and discretionary access control (DAC) features can be used to implement governance policies and classify data. 2. Data Masking: Apply dynamic data masking to protect sensitive information and ensure compliance with regulations like GDPR and HIPAA.

Optimize Data Pipeline:

1. Replace Batch Processing with Real-Time or Micro-Batch Processing: Adopt real-time data processing to improve analytics and decision-making. 2. Utilize Change Data Capture (CDC): Leverage Snowflake features like dynamic tables and streams to minimize transformation overhead and support incremental updates. 3. Orchestrate Workflow with Tasks: Use Snowflake tasks and dependent tasks for workflow automation. For larger deployments, consider tools like Apache Airflow or dbt.

Upskill the Team:

1. Train the Team on Governance Policies: Provide data governance, security practices, and compliance training to ensure a seamless transition. 2. Managing and Monitoring the Cloud Environment: Equip teams with skills to effectively manage and monitor the Snowflake environment for performance and cost optimization.

MONITORING POST-MIGRATION

After migrating to Snowflake, monitoring and optimizing your system is crucial to maximize performance and cost-efficiency. • Query Performance Monitoring: Continuously track the performance of your queries using Snowflake's Query Profile and Query History features. Identify long-running or resource-intensive queries and optimize them to improve system efficiency and user experience. • Fine-Tune Workloads and Frequency to Ensure Cost-Efficiency: Review your scheduled workloads and the frequency of data pipelines. Adjust execution timings and resource allocation to balance performance and cost. Snowflake's dynamic scaling can help allocate resources based on workload demands, ensuring you're not over-provisioning. • Review Unused Data to Optimize Storage Costs: Regularly audit your storage to identify and remove unused or redundant data. Implement data retention policies that archive infrequently accessed data to lower-cost storage options or delete obsolete data. Utilize Snowflake's Time Travel and Fail-safe features wisely to manage historical data without incurring excessive costs.

ENGAGE WITH PARTNERS

Collaborating with experienced partners can streamline the migration process and ensure your organization is fully equipped to harness the power of Snowflake. Engage with certified Snowflake partners who specialize in cloud data migrations. These experts can help design an optimal architecture, manage data transfer securely, and ensure a seamless transition with minimal disruption to business operations. By focusing on monitoring and leveraging expert partnerships, organizations can not only transition smoothly but also unlock the full potential of Snowflake’s cloud data platform.

Summing Up

Migrating enterprise data to the cloud is a significant step toward modernizing business operations. Organizations can ensure a smooth, cost-effective, and secure transition by focusing on the critical areas outlined above and leveraging Snowflake’s innovative features. Connect with us for a free demo, and see how Snowflake can transform your business: https://www.beinex.com/snowflake/

Beinex Shines as a Gold-Level Data Science Consulting Firm in the Middle East 2024

What Sets Us Apart?

Our ranking is based on: • Client & Consultant Reviews: Over 900 client reviews and 2,800+ consultant evaluations. • Industry Expertise: Our deep knowledge of data-driven solutions across sectors. • Reputation & Thought Leadership: Consistent delivery of impactful business solutions. Out of 500+ consulting firms evaluated, only 47 made it to the top, and Beinex stands tall among them.

A Heartfelt Thank You

We owe this milestone to our clients, partners, and team members whose trust and collaboration have been instrumental in our journey. This achievement inspires us to push boundaries and set new benchmarks in Data Science.

About Consultancy-me

Consultancy-me.com is a leading platform for staying updated on the advisory and consulting industry. Their website is dedicated to delivering the latest news and trends across 60+ industries and functional areas within the consultancy sector. As part of the Consultancy.org family, their international network of consulting platforms draws in 4 million visitors per year. Globally, they partner with over 150 leading consulting firms and select companies. The platform serves as a comprehensive resource for professionals interested in consultancy careers, offering insights into job opportunities, graduate schemes, apprenticeships, and internships within the consulting industry.

About Beinex

Beinex is a global firm with businesses on 5 continents specializing in Data, AI, and Digital Transformation. A pioneering enterprise, Beinex has established a powerful presence in the regions it serves by delivering comprehensive solutions to address diverse business challenges in the spheres of Advisory, Technology & Software Development, and Systems Integration. Beinex Consulting caters to a broad spectrum of industries and departments, offering tailored solutions to meet their specific requirements. Beinex excels in a multitude of domains, including Enterprise Data Ecosystem Installation, Data Strategy, Data Roadmap Creation, Technology Roadmap Generation, Data Governance, Data Science Consulting, Data Engineering, Analytics Transformation, Data Monetisation, GRC, as well as other government and business enablement solutions. Feel free to schedule a call with us to explore more about our Data Science services: https://beinex.com/contact-us/

Beinex Gets an Upgrade to Snowflake Services Partner Premier Tier

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:

Beinex can further leverage Snowflake's advanced capabilities and integrate them seamlessly into your solutions.
Enable and empower Digital Transformation at an accelerated pace for our clients with experience and competency of the right kind in accompaniment.
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.

[sc name="quote" quote="“Snowflake has been an integral partner of our digital transformation mission that facilitates end-to-end data cloud solutions we offer our clients at all levels. As a Partner at the Premier Tier, we're geared up to provide our clients with unprecedented power to harness Snowflake's exceptional architecture and revolutionize their data-driven strategies. We are elated”" author="Indumon Das, Managing Director of Beinex"][/sc]

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.