Beinex is Now Great Place to Work-Certified™!

We are delighted to achieve this award with our relentless dedication and unparalleled expertise on the Alteryx platform. With ample product knowledge, technical expertise, and sufficient focus on customer satisfaction, we were able to demonstrate the value that we offer as a partner. Our determination and dedication aided in supplementing our customers with the power to deliver faster and better business outcomes by intelligent decisioning using Alteryx. Last year, we were fortunate enough to successfully transform the majority of our clients’ businesses with Analytic Process Automation by quickly automating analytics and the entire data-driven business processes, resulting in quick wins and faster returns on ROI. We were also awarded with Alteryx 2020 Partner of the Year award, Middle East. With the preferred partner status, we will be able to make even greater collaboration with the Alteryx team, helping us extract its possibilities to the next level. Alteryx always stands for developing data-driven technical solutions to business problems by empowering its clients to be self-sufficient in handling data analytics and continues to provide unmatched services, like;

• • Collecting data from multiple sources for quick analysis and faster insight generation.
  • Exploration of data from on-prem databases, the cloud, and big or small data sets, and more.
  • Analysis with maps, addressing solutions to deeply understand your customers and locations.
  • Augmenting your team’s analytic output to gain insights by using data without any coding or analytics expertise.
  • Embracing automation to effectively communicate with your stakeholders and enable intelligent decision-making to drive better, faster business outcomes.

We are incredibly honored to receive this award, and we look forward to a continued partnership as a preferred partner in 2021! Thank you, Alteryx! About Beinex Consulting Beinex is a digital transformation organization with a broad range of analytics modernization and training services. As a pioneer in analytics and cloud transformation, Beinex’s mission is to transform the way individuals and the organizations work with the data through innovation and experience. Beinex offers a broad range of robust and scalable business intelligence and analytics services to drive effective decision-making and create business value.

Top Differences between Dynamic Set and Fixed Set

Dynamic Set

1. Set members change when the underlying data changes.
2. It has a single dimension.

Fixed Set

1. Set members do not change.
2. It can be single-dimensional or multidimensional.

Steps to Create a Dynamic Set

The process to create a dynamic set is as follows: In the Data pane, right-click on the sub-category dimension and choose Create > Set. (Figure 1)

Figure 1: Creating a Set

• In the Create Set dialog box, set up your set. You can configure it using the following tabs:
1. General: Use the General tab to choose one or multiple values to be considered when computing the set. Alternatively, you can choose the Use All option to consistently consider all members, even when new members are added or removed.

If you know the top-selling products beforehand, you can manually select the products as shown in Figure 2 below.

Figure 2: Creating a Set using General Tab

2. Condition: Utilize the Condition tab to establish criteria that decide which members should be incorporated into the set.

You can specify this condition and create the set if you need products with sales greater than $50,000. (Figure 3)

Figure 3: Creating a Set using Condition Tab

3. Top: Employ the Top tab to set restrictions on which members should be included in the set.

For instance, you can establish a limit based on total sales, where only the top 5 products with the highest sales are included. (Figure 4)

Figure 4: Creating a Set using Top Tab

• Once you have completed the configuration, click the "OK" button.
• The newly created set will appear at the bottom of the Data pane within the Sets section. You can identify it by the set icon, which denotes a set field.

Steps to Create a Fixed Set

The process to create a fixed set is as follows:

• In the developed visualisation, select one or more marks from the view (Figure 5).

Figure 5: Selecting the marks.

• Right-click on the selected mark and select “Create Set” (Figure 6).

Figure 6: Creating the set.

• Type a name for the developed set (Figure 7).

Figure 7: Typing the Set Name.

• When finished, select “OK”. This newly created set can be accessed from the data pane. When this set is placed in the filter, the view will be filtered to show only the relevant set values.

Top Benefits of Sets in Tableau

• Top N or Bottom N Analysis: Sets can filter the data to display only the top or bottom N values based on a specific condition. For example, you could create a set to show the top 10 products by profit or even combine sets and display the top N and bottom N products by profit in a single chart. (Figure 8)

Figure 8: Top 3 and Bottom 3 Products by Profit

• Segmentation Analysis: Sets can also segment data into groups based on a specific condition. This can be useful for analysing performance differences between different groups. For example, you could create a set to segment customers based on their geographic location.

• Excluding Data: Sets can be used to exclude specific data points from a visualisation. For example, you could create a set to exclude customers who have not purchased in the last six months.

What is Set Actions in Tableau

Set actions allow users to modify the values within a set, on selection of marks within a view. This enables your audience to engage directly with a visualisation or dashboard and control various aspects of their analysis.

To utilise set actions:

1. Create sets associated with your data source.
2. Build set actions using the created sets.
3. Optionally, create calculated fields that incorporate the sets.
4. Construct visualisations referencing the sets.
5. Test and adjust the set actions for desired behaviour.

To create a set action that helps in drilling down category:

1. Create a set that selects a particular category (Figure 9 shows creating a set using the general tab selecting only furniture)

Figure 9: Creating Category Set using General Tab

2. If you are in a worksheet, go to Worksheet > Actions.
If you are in a dashboard, go to Dashboard > Actions.

3. In the Actions dialog box, click “Add Action” and choose "Change Set Values."

4. In the Add/Edit Set Action dialog box:

• Provide a descriptive name for the action.
• Choose a source sheet or data source. By default, the current sheet is selected. If you opt for a data source or dashboard, you can select specific sheets within it.
• Choose the desired method for users to execute the action:

1. Hover: The action will trigger when a user hovers the mouse cursor over a mark in the view.
2. Select: The action will activate when a user clicks a mark in the view.
3. Menu: The action will initiate when a user right-clicks (or control-click on Mac) a selected mark in the view and then selects an option from the context menu.

• To specify the target set:

1. First, choose the data source from the available options.
2. Then, select the desired set from the Target Setlist.

Figure 10: Setting up set action

• Specify what happens when the action is run in the view:

1. Assign values to set - Replaces all values in the set with selected values.
2. Add values to set - Adds individually selected values to the set.
3. Remove values from the set - Removes individually selected values from the set

• When the selection is cleared in the view:

1. "Keep set values" will retain the current values in the set without any changes.
2. "Add all values to set" will include all possible values in the set.
3. "Remove all values from set" will remove all previously selected values from the set.

5. After configuring the desired behaviour, click "OK" to save the changes and return to the view.
6. To ensure the set action functions as intended, interact with the visualisation, and test its behaviour.

Benefits of Set Actions

1. Filtering: Set actions can filter data based on user selections. For example, you could create a set step that filters the data to show only the top 10 customers in a particular region.
2. Highlighting: Set actions can also highlight data based on user selections. For example, you could create a set action highlighting all the customers who have purchased in a particular month.
3. Drill-downs: Set actions can create drill-downs that allow users to explore the data in greater detail. For example, you could create a set action enabling users to drill down from a high-level view of category by sales to a more detailed view of sales by sub-category. (Figure 11)

Benefits: Enhanced Data Cloud Capabilities

The partnership will let Beinex turbocharge services on the AI-ML, analytics fronts by utilising storage and compute scalability unlocked by the unique collaboration. It awards Beinex and its clients the capability to flourish in terms of cost leadership, domain leadership and added utilisation of potential in sync with market conditions.

Data marketplace enhancement

The partnership also means that acquiring and testing third-party data is now easier which also entails the Snowflake users to imbibe the expanded third-party data into their environment, attach it to their first-party data and evaluate the data efficacy vis-à-vis customer experience along with the impact it can create.

There is little doubt that the capability is very much in demand as Beinex clients are into delivering powerful customer/ user experience as a part of their service efforts

Features:

• Privacy-safe
• Secure sharing platform
• No need to set up extra secure portals to support sharing of Personally Identifiable Information

UAE data residency requirements are also met thanks to the Snowflake domestic capacity.

The power of partnership

Beinex partnership with Snowflake enables it to offer clients advanced features like automated tuning and elastic compute with unlimited decoupled computing capability, along with the analytics modernization services, to help organisations realise exponential Return on Investment. This upgrade in status will take business to the next level for both Beinex and its esteemed client line-up.

Partnerships are what make Beinex stronger. The company has strong partnerships with some of the leading technology firms, research labs, and universities around the globe.

Businesses can leverage the power of our partner ecosystem to maximize the value of their end-to-end analytics journey.

Beinex is ecstatic to receive this recognition as a Snowflake select services tier partner and is grateful to Snowflake for acknowledging its client services.

1. Start with Storage Using Amazon S3

Amazon S3 is a secure and reliable storage solution when you are dealing with massive datasets. It's highly scalable, extremely durable, and serves as a foundation for most data workflows. You can depend on it from initial data landing zones to backup archives.

2. Spin Up Power with Amazon EC2

When you need raw computing power for heavy-duty tasks, such as batch processing or running data pipelines, EC2 gives you the flexibility to choose instance types suitable for your workloads. You're in control of the compute environment, which is key for tuning performance.

3. Simplify ETL with AWS Glue

Managing extract-transform-load operations can be messy. AWS Glue resolves this with automated data discovery, code generation, and job orchestration. AWS Glue can support you if you're managing multi-source ingestion and need to clean and prepare your data for use.

4. Query at Speed with Amazon Redshift

Redshift offers the easiest and quickest way to run complex queries against large volumes of structured data. It's perfect for powering dashboards, reports, and business intelligence tools without the drag of traditional databases.

5. Tackle Big Data with Amazon EMR

If your workloads involve distributed computing using Apache Spark or Hadoop, EMR helps you deploy and manage those clusters in a fraction of the time. It is ideal for advanced data transformations and machine learning (ML) workloads, as it integrates easily with other AWS services.

6. Event-Driven Logic with AWS Lambda

Forget provisioning servers to process a few files. Lambda allows you to write lightweight, trigger-based code that responds to data events. It is an efficient serverless solution for processing files as they arrive or triggering downstream processes.

7. Streamline Real-Time Data with Amazon Kinesis

Modern data doesn't always arrive in neat batches; it streams in constantly. Kinesis helps you manage this chaos by capturing, processing, and analyzing real-time data. You can utilize it for use cases such as log monitoring, clickstream analysis, and sensor data processing.

8. Store Fast & Flexible Data with DynamoDB

DynamoDB is a fully managed, serverless database ideal for workloads where speed and uptime are paramount. It provides a NoSQL solution that works best in situations where low latency is essential, such as recommendation engines or personalized content delivery.

9. Keep Your Metadata in Check: Glue Data Catalog

The Glue Data Catalog can be considered as a metadata hub that consolidates information regarding datasets, schemas, and transformations for you. It improves discoverability and governance—two things no engineer should overlook.

10. Coordinate Workflows with AWS Step Functions

As you know, data workflows can span multiple tools, services, and dependencies. AWS Step Functions help you string those steps together into one cohesive flow, complete with retries and error handling. It's a visual way to orchestrate and manage complex processes with clarity and ease.

Best Practices for Using AWS Tools as a Data Engineer

AWS tools are powerful, but knowing what to use isn’t enough; how you use them is what drives real impact. That’s where the best practices for using AWS services come in:

• Scalability: Use services that grow with your data. Enable auto-scaling in EC2, EMR, and Lambda to handle variable workloads.
• Automation: Set up Glue jobs, Lambda triggers, and Step Functions to run tasks without manual effort.
• Security: Encrypt your data (both at rest and in transit) and adhere to least-privilege access with IAM roles.
• Cost Monitoring: Use spot instances, archive old data in S3 Glacier, and monitor costs with AWS Budgets.
• Smart Workflows: Break pipelines into smaller, reusable steps. Use Step Functions for clear orchestration.
• Track & Monitor Everything: Use CloudWatch and CloudTrail to keep an eye on performance, errors, and user actions.
• Organize Metadata: Keep your Glue Data Catalog updated and use clear naming so your data is easy to find and understand.
• Test Before You Trust: Validate your data and test your pipelines with sample loads before pushing to production.
• Document as You Go: You can easily maintain notes on your workflows, data sources, and transformations for smoother teamwork.

Wrapping Up: Why These Services Matter

Tools that enable speed, flexibility, and automation are not just desirable; they're essential. AWS offers a comprehensive toolkit that covers all stages of the data lifecycle. By staying up to date with these services, you not only improve your performance at work but also position yourself to take the lead in a data-driven, cloud-first future.

For data engineers seeking to excel in their roles, it is beneficial to become proficient in at least 10 AWS services. By serving as the foundation for scalable and effective data pipelines, these services help businesses transform unstructured data into actionable insights. Data engineers can significantly contribute to fostering innovation and informed decision-making within their companies by leveraging the potential of Amazon Web Services.

What is Generative AI

Generative AI is a subfield of Artificial Intelligence that utilizes patterns found in vast databases to produce original content, including text, images, music, and videos. GenAI aims to provide creative and human-like outputs, in contrast to classical AI, which primarily makes predictions or classifies data. Generative AI models, such as OpenAI's ChatGPT and DALL-E, utilize sophisticated neural networks, specifically transformer architecture, to produce content that is logical and sensitive.

Industries are transforming with the help of generative AI, and its benefits are innumerable. Marketers are using it to automate campaigns and generate personalized content at scale, while writers and creators rely on it to spark ideas and accelerate production. In healthcare, it's being explored for diagnostics, treatment planning, and medical research. At its core, Generative AI isn't just a tool; it's a transformative force reshaping how we create, innovate, and solve complex problems across sectors.

GenAI Solutions in the UAE

The Generative AI market in the UAE is on an impressive growth trajectory. Currently, the market is estimated to have reached USD 220 million and is expected to surpass USD 1.3 billion by 2030, growing at a CAGR of over 35%. With the UAE's commitment to becoming an AI-driven economy, including initiatives such as the UAE National AI Strategy 2031, the region is emerging as a hub for AI adoption and innovation.

Top 10 Benefits of Generative AI

Generative AI is reshaping how businesses create, operate, and innovate. Here are the top ten key benefits of GenAI that you can leverage for your business:

1. Automates Content Creation

Generative AI tools streamline content development, including blog posts, ad copy, social media content, and other types of content. Marketing teams use AI to generate drafts, brainstorm ideas, and iterate quickly. It speeds up production, improves quality through iterative feedback, and reduces the need for hiring additional staff. GenAI tools can craft landing page content or email campaigns that effectively highlight your brand's voice.

2. Delivers Hyper-Personalized Experiences

AI leverages customer and product data to generate personalized recommendations and messaging. In e-commerce, this can mean showing the right product to the right user at the right time. Personalized AI outputs enhance engagement and conversion rates.

To ensure ethical outcomes, businesses are auditing training datasets to prevent bias, which is particularly crucial in sensitive sectors such as healthcare, finance, and hiring.

3. Enhances Product Design and Innovation

AI models analyze market trends and customer behavior to guide product development. By processing vast datasets, they uncover unmet needs and help generate concepts that align with evolving consumer preferences. Many GenAI tools aid in rapid prototyping and idea testing.

4. Strengthens Cybersecurity

Generative AI boosts threat detection by identifying anomalies in network traffic and alerting teams in real time. It excels at identifying phishing patterns, malware signatures, and unusual behaviors more quickly than manual reviews. As attackers also begin using AI, this defense becomes increasingly critical.

5. Accelerates Healthcare Research

Generative AI is expediting drug discovery and diagnostics. AI also allows the generation of synthetic patient data, facilitating preclinical testing without privacy risks. It shortens development timelines and supports personalized medicine by analyzing genetic and clinical datasets. It can also predict diseases before they strike us.

Read Our AI in Healthcare Case Study on Cardiovascular Disease Prevention!

6. Streamlines Business Processes

AI automates repetitive tasks such as summarizing reports, drafting emails, or analyzing PDFs. GenAI Tools allow teams to focus on strategic work rather than data wrangling. For example, HR teams can auto-generate job descriptions, and sales teams can craft personalized follow-up emails using AI.

Book a Free Demo of Our Document Chatbot

7. Improves Customer Support

Generative AI chatbots offer 24/7 support, providing context-aware responses to resolve queries. Unlike traditional bots, these systems adapt in real time, understand tone, and escalate issues when necessary. Businesses utilize various tools to achieve faster resolution times and higher satisfaction scores.

8. Accelerates Market Innovation

By analyzing market signals, customer behavior, and industry shifts, AI uncovers opportunities for product, service, or business model innovation. It reduces risk and helps companies make data-backed decisions about where to invest. AI can forecast trends and simulate outcomes before committing resources, allowing for informed decision-making.

9. Drives Digital Transformation

AI encourages traditional industries, like oil & gas, construction, logistics, and agriculture, to adopt technology by demonstrating clear ROI. Predictive maintenance, supply chain optimization, and workflow automation are just a few areas where AI proves valuable. It helps leaders make faster, more informed decisions, accelerating digital adoption.

10. Accelerates Creative Innovation

Generative AI serves as a brainstorming partner. Designers utilize tools like Midjourney for rapid visual prototyping, while writers and product teams employ chatbots to refine their ideas. These tools provide novel starting points, enabling creators to break through mental blocks and explore new directions more quickly.

Summing Up

Beinex GenAI Solutions is at the forefront of transformation, helping organizations in the UAE explore the full potential of generative AI. As one of the recipients of the Dubai AI seal, Beinex is enabling businesses to innovate faster and operate smarter, from automating content generation to creating intelligent decision-making systems. Businesses that adopt it strategically are gaining a competitive edge, not just by saving time, but by reimagining what's possible.

Explore Beinex GenAI Solutions!