Uncovering Data Sharing

Traditional data-sharing methods involve copying files via FTP/cloud, employing ETL pipelines, or utilising APIs. While these methods facilitate data exchange, they come with inherent limitations. Security vulnerabilities, data inaccuracies, and high maintenance costs are just a few of the challenges organisations face. Snowflake's Secure Data Sharing offers a standard shift by enabling seamless, governed access to data within the Snowflake platform.

Secure Data Sharing

Secure data sharing is ideal for granting raw data access across business units or to trusted partners for analysis. It fosters informed decision-making and facilitates data monetisation by providing secure, revocable access to valuable datasets.

Snowflake's Role in Secure Data Sharing

Snowflake's Cloud Data Platform empowers organisations to collaborate securely, driving cost savings and uncovering new insights. With Snowflake Secure Data Sharing, businesses can:

Access live data across the organisation swiftly.

Exercise controlled, governed access to shared data.

Publish datasets for discovery while maintaining access controls.

Introducing Data Clean Rooms

In the era of heightened data privacy concerns, data clean rooms emerge as a game-changer. Unlike traditional clean rooms, modern data clean rooms go beyond physical boundaries. They operate as a framework, eliminating the need to relocate data. In essence, a data clean room allows providers to dictate query rules without granting access to underlying data.

When to Opt for Data Clean Rooms

While secure data sharing suffices for many collaborations, data clean rooms shine in scenarios involving sensitive or regulated data. Regulations like CCPA and GDPR mandate stringent privacy adherence, making data clean rooms indispensable for privacy-preserving collaboration. For industries like media and advertising, data clean rooms enable personalised insights without compromising consumer privacy.

Snowflake Global Data Clean Room

Snowflake Global Data Clean Room revolutionises multi-party collaboration by safeguarding data privacy. Leveraging Snowflake's robust collaboration and governance features, it facilitates secure analysis across clouds and regions, mitigating the risk of data exposure or re-identification.

Choosing the Right Approach

In navigating data collaboration, enterprises must prioritise security and compliance. While Snowflake Secure Data Sharing suits low-risk collaborations, data clean rooms are indispensable for handling sensitive or regulated data. By embracing these innovative solutions, businesses can foster a culture of secure collaboration, driving insights and innovation while safeguarding data privacy.

Snowflake Data Sharing

Data sharing in Snowflake equips you to share specific objects with another Snowflake account or a designated reader account. The beauty of this process lies in the fact that the data isn't duplicated or moved between accounts.
Now, why is this a game-changer for organisations? When constructing data pipelines and developing data products, it's a common practice to shuttle data between databases and diverse systems to blend different datasets.
Consider this scenario: You have transactional data within your online transactional processing (OLTP) database, and you wish to integrate it with external data for a machine learning model. Traditionally, organizations would export data into a data lake, import external data, and then employ tools like Apache Spark for analysis.
But what if, instead, you could simply deposit your data into Snowflake, and the external data source could seamlessly share its data with your organisation, eliminating the need to load it separately? This eradicates the challenge of keeping data copies synchronised, resulting in savings on storage, computing costs, and maintenance efforts.
Imagine your company possesses valuable information that can guide other companies in making informed decisions. For instance, let's say your company can provide precise estimates for product delivery times based on proprietary data, and you want to offer this information for sale to your customers.
Enter Snowflake data sharing—it empowers you to precisely do that.

Case Studies: Snowflake Data Sharing

Citing two instances where leading organisations use Snowflake to improve actionable data sharing, collaboration and reporting capabilities.

1. A Pioneering Technology Leader A well-known Swedish-Swiss multinational corporation successfully implemented a streamlined data strategy using the Snowflake Data Cloud, adopting an "extract once, use everywhere" approach that simplified data consolidation and enablement. By transitioning from nightly extracts, which caused significant system overhead, to a single, near real-time Change Data Capture (CDC) process, the company achieved efficient replication of information to Snowflake with minimal impact. The utilisation of Snowflake Secure Data Sharing facilitated secure and governed data collaboration across the four business areas.
2. A Leading fast-food Restaurant Chain Snowflake's data-sharing capabilities have revolutionised decision-making for a fast-food restaurant chain. They can effortlessly share crucial sales, inventory, and operational data with external entities, expanding from three to over 30 parties.
With a high-performance database platform hosting over 2 million transaction records, the restaurant chain has established a robust data management and analysis infrastructure through Snowflake, empowering its operational and marketing endeavours.
Moreover, by consolidating all data onto Snowflake, the organisation has achieved a remarkable 70% reduction in operational IT costs, demonstrating the platform's efficiency and cost-effectiveness.
Centralising and sharing data with Snowflake significantly eased the development of data products for various purposes, including marketing campaign analytics, quotation success metrics, production line tools, and supply chain dashboards. These data products are utilised by thousands of users globally, including internal stakeholders and external vendors, enhancing collaboration and efficiency across the organisation.

What are the best practices for Snowflake data sharing?

Optimize your Snowflake data sharing experience with these essential practices. Ensure data security by utilizing secure views to filter and mask sensitive information. Enhance clarity and understanding by employing descriptive names and comments for your shares. Monitor and fine-tune your sharing activities using Snowflake Information Schema or Account Usage views. Foster communication and collaboration with your consumers to create a seamless workflow.
Take command of your data sharing environment by setting quotas and limits with the ALTER SHARE command. Keep your consumers informed about any changes or updates to your shares, and actively seek feedback to refine your data-sharing strategy. Explore additional data sources through Snowflake Data Exchange or Data Marketplace to enrich your analytics.
These best practices safeguard sensitive data, ensure compliance with data privacy regulations, clarify the purpose of each share, and provide insights into usage and performance, ultimately enhancing your data analysis capabilities. Below are some best practices for data sharing with Snowflake:

1. Understand Snowflake Data Sharing
Familiarize yourself with Snowflake's data sharing features, such as Secure Data Sharing (SDS) and Sharehouse, to leverage the platform effectively.

2. Role-Based Access Control (RBAC)
Implement strong RBAC policies to control who can share data and who can access shared data. Define roles and permissions to ensure data security and compliance.

3. Secure Data Sharing
Use Secure Data Sharing (SDS) to securely share data with external parties without copying or moving the data. Implement encryption and access controls to protect sensitive information.

4. Sharehouse Best Practices
If using Sharehouse, follow best practices for creating and managing share objects. This includes defining share schemas, tables, and using the appropriate share options for your use case.

5. Data Masking and Redaction
Apply data masking or redaction policies to shared data to protect sensitive information. Ensure that shared data complies with privacy regulations and internal data governance policies.

6. Query Performance Optimization
Optimize query performance for shared data by using clustering keys, partitioning, and indexing. This helps enhance the efficiency of queries on large datasets.

7. Versioning and Change Tracking
Implement versioning and change tracking mechanisms to keep track of updates and changes in shared data. This ensures data lineage and helps with auditing and troubleshooting.

8. Documentation and Metadata
Maintain comprehensive documentation and metadata for shared datasets. Include information about the source, purpose, and any transformations applied. This helps users understand the shared data context.

9. Governance and Monitoring
Establish governance practices for data sharing, including regular reviews of shared data objects and access logs. Monitor data-sharing activities to identify any anomalies or potential security issues.

10. Educate Users
Provide training and documentation for users involved in data-sharing activities. Ensure they understand the best practices, security protocols, and the impact of data sharing on performance.

11. Regular Audits and Reviews
Conduct regular audits and reviews of shared data objects, permissions, and access controls. This helps maintain data integrity, security, and compliance with organizational policies.

12. Cost Monitoring

Keep an eye on the costs associated with data sharing, especially if you're sharing data externally. Understand the pricing model and optimize data sharing configurations to manage costs effectively.

By adhering to these best practices, you can:
1. Shield Sensitive Data: Employ secure views to fortify sensitive information.
2. Navigate Data Privacy Regulations: Ensure compliance with data privacy regulations by controlling access and usage.
3. Illuminate the Purpose of Each Share: Maintain transparency regarding the intended purpose and content of each shared dataset.
4. Efficiently Monitor Usage and Performance: Keep a finger on the pulse of usage patterns and optimize performance for streamlined data sharing.
5. Elevate Your Data Analysis Journey: Enrich your analytics by exploring diverse data sources and unlocking fresh perspectives.

What’s Next

1. Enhanced Data Collaboration Tools:

Snowflake is expected to introduce advanced features for more streamlined and efficient data collaboration, addressing the evolving needs of industries.

2. Innovations for Privacy-Preserving Analytics:

Snowflake aims to develop and implement solutions that uphold data privacy while enabling powerful analytics, aligning with the growing concerns in this area.

3. Adaptation to Changing Industry Dynamics:

Snowflake is likely to evolve its platform to meet the challenges posed by changes in industry dynamics, ensuring it remains a robust solution for data management and collaboration.

4. Integration of Cutting-Edge Technologies:

Snowflake may integrate emerging technologies, enhancing its capabilities to support new use cases and data-intensive analytic methods.

5. Continued Emphasis on Secure Data Collaboration:

Future updates from Snowflake may include even more robust security measures and innovations in data clean rooms, reflecting a commitment to secure data collaboration in the face of a dynamic data landscape.

Best Way to Share Data for Your Business

For secure collaboration, old ways of copying data are no longer the best. If you're working with trusted partners and it's privacy-compliant, Snowflake Secure Data Sharing is a quick and secure option. But, if you're dealing with sensitive or regulated data, especially when the risk is high, consider using a data clean room for an extra layer of security and compliance.

Beinex + Snowflake Offerings

Beinex’s 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.

Four Ways Alteryx Automation and AI Can Transform Your Marketing Strategy:

While there are numerous objectives marketing teams can achieve with data analytics, this blog highlights four ways Alteryx automation and AI can transform your marketing strategy:

Centralize Your Data

Enhance Your Marketing Campaigns

Maximize Your Talent and Resources

Achieve Immediate Results While Preparing for the Future

1. Centralize Your Data

As the marketing landscape prepares for a cookie-less future, having a unified view of your data is essential. Staying ahead of customer needs, competition, and campaigns requires gathering all your data in one place.
With analytics automation, you can easily integrate data from various sources—whether cloud or on-premises, first-party data, or marketing applications like web analytics and CRMs—to gain a comprehensive view of your customers. This enables marketing teams to react to market shifts in real time.

Use case:

For example, a multinational retailer leveraged analytics automation to bring together data from all customer interactions, resulting in a 37x improvement in processing efficiency. This allowed them to better understand customer behavior across multiple channels.
Unlike traditional spreadsheets, which have limitations on data capacity, analytics automation platforms offer limitless capabilities, allowing you to manage vast amounts of customer and product data in one place.

How Alteryx Helps:

• Drag-and-Drop Data Integration: Simplify complex data workflows with easy-to-use, drag-and-drop tools that eliminate manual coding and reduce time to insight.
• Automated Data Cleaning: Utilize pre-built data preparation tools to clean, standardize, and transform data in just a few clicks, ensuring high-quality data for analysis.
• Cluster Analysis: Automatically group similar data points (e.g., customer segments) using clustering tools, enabling precise targeting and personalization without manual intervention.

2. Enhance Your Marketing Campaigns

Marketing success depends on speed and agility, especially when it comes to predicting market trends and competitor behavior. Optimizing targeting, pricing, or strategy without the right insights becomes a challenge. Analytics automation helps you find the right combination of offers and tactics to increase conversions and boost revenue.

Use Case:

A retail chain with 500+ stores struggled to predict customer buying patterns and optimize promotions. By implementing analytics automation, they processed customer data in real time, enabling hyper-personalized marketing campaigns that boosted conversion rates by 35%.
They also used machine learning to predict demand and optimize inventory, preventing stockouts during key promotions. Additionally, they automated pricing analysis, reducing adjustment times from weeks to hours. By integrating spatial analytics, they could identify high-performing stores and strategically allocate resources, further enhancing their marketing and sales efforts. They also automated pricing analysis based on regional market dynamics, reducing adjustment times from weeks to hours and ensuring competitive pricing across all locations.

How Alteryx Helps:

• Predictive Modeling: Leverage machine learning models to forecast demand, optimize pricing strategies, and predict customer churn, allowing for proactive campaign adjustments. • Market Basket Analysis: Identify products that are frequently purchased together to optimize cross-selling and upselling opportunities, increasing revenue per customer. • Real-Time Analytics: Process large volumes of data in real-time to quickly adjust marketing strategies and promotional offers based on current performance metrics. • Spatial Analytics: By analyzing geographic data, marketing teams can optimize store placements, allocate resources more effectively, and improve overall sales performance.

3. Maximize Your Talent and Resources

Many marketing teams struggle to turn data into valuable business insights. According to Gartner, only 53% of marketing decisions are informed by data analytics. Limited staff and time often prevent teams from fully utilizing their data potential.
Analytics automation bridges this gap by enabling teams to achieve more with fewer resources. It automates the time-consuming tasks of data cleaning and preparation, allowing marketing teams to save significant hours and focus on more strategic projects.

Use Case:

For example, a leading digital advertising agency transitioned from using spreadsheets for social media analysis to implementing analytics automation. This resulted in a 99.5% faster analysis, saving 180 weekly analyst hours. By automating routine tasks, your team can dedicate more time to high-impact initiatives, ultimately enhancing overall business value.

How Alteryx Helps:

• Self-Service Analytics: Empower non-technical users to perform complex data analyses without relying on IT or data science teams, accelerating time to insight. • Workflow Automation: Automate repetitive tasks like data cleansing, transformation, and reporting, significantly reducing manual effort and minimizing the risk of errors. • Scalable Solutions: Handle vast amounts of data effortlessly, allowing your team to focus on high-impact projects without being bogged down by data management issues.

4. Achieve Immediate Results While Preparing for the Future

Marketing leaders often juggle the challenge of balancing short-term returns with long-term strategic goals. Analytics automation solutions can provide quick wins while also laying a foundation for future success.
By choosing a solution that is user-friendly and easy to implement, you can skip lengthy training sessions and start seeing results quickly. Moreover, the best analytics tools are designed with the future in mind, offering integration with cloud services and AI-driven insights.

Use Case:

For example, a premier company specializing in technology services, utilized analytics automation to analyze 250 broadcast campaigns, resulting in an 88% time savings and a 25% increase in time spent on advanced analytics. The right automation tools not only generate fast results but also ensure you're ready for future growth.

How Alteryx Helps:

• Quick Implementation: Start generating insights rapidly with intuitive tools that require minimal training. Alteryx’s user-friendly interface means your team can hit the ground running without lengthy onboarding sessions. • Future-Ready Integration: Alteryx seamlessly integrates with cloud services, AI platforms, and advanced analytics tools, ensuring your marketing strategy evolves alongside technological advancements. • Comprehensive Analytics Suite: From spatial analysis to text mining, Alteryx provides a wide range of analytical tools that help you address complex business questions and prepare for emerging trends.

How Marketing Teams Can Benefit from Alteryx

With Alteryx, marketing teams can benefit from:
• Self-Service Analytics: A user-friendly, drag-and-drop interface, you can easily access and analyze data without technical expertise. • Pre-Built Analytical Tools: Utilize pre-configured tools for market basket analysis, spatial analytics, and more without needing custom development. • Seamless Integration: Integrate Alteryx with your existing marketing tech stack for a cohesive, end-to-end analytics solution.

Alteryx+ Beinex Offerings

Our Premier partnership with Alteryx empowers business users to automate manual data cleansing and transformation tasks in minutes through a simple visual workflow while incorporating the latest technological advancements.
Connect with us for a free demo: https://beinex.com/alteryx-partner/

[sc name="quote" quote="“As a practitioner, I believe that the major game changer in the latest version, Tableau 2023.1, is Accelerator Data Mapping. With Data Mapping you can jump-start your analytics even faster by reducing the time and effort required to set up an Accelerator’s ready-to-use dashboards. Now, when configuring an Accelerator, the Data Mapper allows users to pull outside data into the Accelerator and map fields from their data source into the fields the Accelerator expects. This will be made possible via the Data Mapping UI - a hybrid dialogue box that opens by default with any Data Mapping enabled Accelerator”" author="Sanchit Katiyar, Solution Architect at Beinex."][/sc]

Let’s catch up with Tableau’s brand-new capabilities:

1. Tableau for Slack Enhancements

The Tableau app for Slack has been improved to enhance collaboration on insights. These updates make it simpler to prioritize data in every conversation and decision. New features include the ability to share Tableau content with context using link previews, which helps teams quickly identify and act on pertinent information. Additionally, it's now easier to search for and share Tableau content in direct messages and channels. Finally, you can quickly access your recent and favourite items from the App homepage, making it faster to get to insights.

2. Identity Pools for Tableau Server

Identity Pools provide a way to go beyond the current restriction of having only one identity store on the Tableau Server. An Identity Pool consists of a "Source of Users" (previously known as the Identity Store) and an authentication mechanism. With this feature, you can add more pools where your source of users can belong to a local identity store and authenticate using OpenID Connect for modern authentication. This added flexibility will benefit organizations that have external users who need access to Tableau but cannot be added to their corporate Active Directory.

3. Dynamically Update Axis Titles

Parameters are useful for adding interactivity and flexibility to a visualization. They allow viewers to select how they want to view the data. However, previously, it was not possible to automatically update the axis title.
Dynamic axis titles enable the axis title to be determined by the value of a parameter or a single-value field. This feature allows authors to provide better context for their data visualizations to their audience.

4. Support Internal and External Users on Tableau Server

If you've found the single identity store limitation of Tableau Server to be limiting, you'll be pleased to know that Identity Pools offer a solution. In the past, there were only two types of identity stores, local and external, and changing the configuration required a complete reinstall of the Tableau Server.
Identity Pools allow you to overcome this limitation by creating additional pools that combine a "Source of Users" (previously known as the Identity Store) and an authentication mechanism. You can now have your source of users belonging to a local identity store and authenticate using OpenID Connect for modern authentication. This added flexibility allows you to support both internal and external users who are not part of the corporate Active Directory.

5. Personalize Data Access with User Attributes

The new USER ATTRIBUTE (string) function is now available for personalized data access. This function passes login attributes in a calculation, which can be used as a data source filter for row-level security, beyond just username and group, such as department or region. This allows for the customization of a user's data access in embedded scenarios.
With this new function, you can include additional information about users and send it to Tableau when the users sign in. Tableau will automatically use this information as a filter, only showing corresponding data to the user.
When the filter is applied in your workbook or dashboard, Tableau searches for the value of the attribute in the viewing user's authentication token. Using Connected Apps and SSO for embedding users, you can include the attribute as a claim in the JSON Web Token (JWT) used for user authentication.

How Tableau 2023.1 can be Beneficial to the Tableau Users

With the added new features, you can enjoy the advantages enlisted below:

1. Greater Flexibility and Security for Both Internal and External Users: Tableau Server now offers greater flexibility and security for both internal and external users with the ability to add local identity stores and authenticate using OpenID Connect.
2. Efficient Offline Environment Management: With an enhanced activation solution, managing offline environments is a breeze, thanks to the option to leverage login-based license management.
3. Reliable Tableau Mobile: Tableau Mobile is now even more secure, due to added security policies that prevent screen sharing and screenshots on Android devices, as well as the detection of jailbreak and malware.
4. Connect to Google BigQuery: Connecting to Google BigQuery is now more efficient than ever, be the new JDBC connector that uses BigQuery's Storage API.
5. Resource Monitoring Tool: The tool, which is a component of Tableau Advanced Management, now comes with enhanced features that make logging in easier and allow for more customization options:
6. Network Credentials Support: Users can now use their network credentials to log into the Resource Monitoring Tool instead of using a distinct username and password.
7. Customizable Run As users: With this new feature, you can set up Run As users for the Resource Monitoring Tool Server and Agent on Linux operating systems to comply with your security policies and apply best practices.
8. Tableau Data Management now offers enhanced features that enhance data reliability and flexibility for virtual connections:
9. Data Warnings: Data quality warnings are now available in both web authoring and Data Details to help improve data trust. Users can receive warnings about data quality at the column level.
10. Flexible Connectivity: With the latest update, users can choose to use either a live or extract connection for each table within a virtual connection. This allows them to refresh the data as needed to suit their needs.

Are you as excited as we are about these amazing new features? If so, be sure to get started with Tableau 2023.1 today!

About Beinex+ Tableau Partnership

As a quick, versatile, and easy-to-use self-service platform tailored to your organisational needs, Tableau streamlines the power of data. It enables users to make decisions more quickly and with greater confidence from anywhere, anytime.
As a premium partner, Beinex offers the best of Tableau services to grow your business. Our partnership with Tableau has unveiled several seamless possibilities for businesses. Tableau, with its user-friendliness, makes Data Analysis and Visualization an enjoyable, interesting and rewarding process.

Explore the power of Beinex + Tableau, now: https://www.beinex.com/tableau-partnership-and-consulting-services/

Tableau Exchange: A One-stop Destination

You can access Tableau Accelerators through Tableau Exchange. Tableau Exchange is a platform where the Developer Community can showcase and offer a wide range of dashboard extensions, connectors, and accelerators. It is your all-in-one destination for offerings that accelerate your data analysis, providing prompt insights and actionable data. This platform offers a wide range of trusted solutions created by Tableau and our partner network, enabling faster time to value, catering to various use cases, and maximising your Tableau investment returns.

What exactly are Tableau Accelerators?

Tableau Accelerators are pre-built dashboards and workbooks created by industry and functional experts, allowing you to leverage analytics tailored to your specific line of business, vertical, or sector. Instead of starting from scratch, you can begin with these expert-built dashboards for various industry and departmental use cases, accelerating your data-driven insights. These pre-built assets are designed to monitor and enhance key performance indicators (KPIs) across your entire organisation.

For instance, Tableau’s healthcare offerings have introduced Accelerators that delve into metrics such as patient wait times, admission rate seasonality, readmission rates, and more. In addition to industry-specific dashboards, Tableau offers a multitude of Accelerators for various lines of business functions like marketing, sales, and corporate finance. Tableau also provides Accelerators that seamlessly integrate with critical enterprise applications and cloud services such as Salesforce, Marketo, LinkedIn, and Service Now.

How to use Tableau Accelerators? Steps

To begin utilising Tableau Accelerators, follow these steps:

1. Visit exchange.tableau.com/accelerators.
2. Once on the website, you can easily browse and filter the available Accelerators based on your specific requirements. You have the option to filter by Tableau version, connection type, language, industry, or job function.
3. Each Accelerator listing provides detailed information about how to use the dashboard effectively. It includes insights on the business questions the dashboard can address, the necessary attributes for optimal performance, demo scenarios, and even potential partners who can assist in customising the Accelerator to suit your specific requirements.

By following these simple steps, you can access the Tableau Accelerators that best align with your goals, helping you jumpstart your data analysis and derive valuable insights.

Types of Tableau Accelerators

Tableau accelerators offer valuable solutions in various fields, addressing specific industry needs and challenges. With their versatility and industry-specific capabilities, Tableau accelerators provide valuable insights and empower data-driven decision-making in various fields like corporate finance, healthcare, ESG, insurance, marketing, public sector, retail, telecommunications, supply chain and manufacturing etc.

1. Corporate Finance

The Corporate Finance Accelerator by Tableau offers finance professionals a range of powerful tools. It enables in-depth financial analysis, facilitates budgeting and forecasting, and streamlines the generation of financial reports. With this accelerator, finance teams can gain valuable insights, make informed decisions, and effectively manage the financial aspects of their organisation.

Examples of corporate finance accelerators:

a. Budget Controlling Accelerator


Budget Controlling Tableau Accelerator provides the capability to:

• • Evaluate and manage your budget expenditure effectively.
• • Analyse budget consumption from various viewpoints, including Month-to-Date, Year-to-Date, and Actual figures, and compare against the budget and the previous year, all presented in a tabular format.

b. Budget Allocation Accelerator

Using Budget Allocation Accelerator by Beinex, you can:

• • Offers a clear comparison of revenue and expenses against the budget.
• • Enables you to track the trends of revenue and expenses over time.
• • Analyses revenue and expenses by vendor, economic sector, account group, and geography.
• • Allows you to drill down into individual customer details for a more detailed understanding.
• • Makes actionable decisions based on the insights gained from the accelerator.

2. ESG (Environmental, Social, and Governance)

In the realm of ESG, Tableau accelerators enable organisations to visualise and analyse environmental, social, and governance metrics, track performance, and benchmark against industry standards.

An example of an ESG accelerator is given below:

a. ESG by Tableau

With this Tableau Accelerator, you can:

• • Evaluate global efforts in Environment, Social, and Governance (ESG) areas.
• • Analyze detailed environmental indicators.
• • Assess leading industries in terms of ESG performance.
• • Deep-dive into specific companies and benchmark their performance against competitors.

3. Healthcare

Tableau accelerators in healthcare help analyse patient data, optimise resource allocation, and enhance decision-making for improved healthcare delivery in healthcare.

An example of a healthcare accelerator is provided:

a. Budget Controlling

With this Tableau Accelerator, you can:

• • Evaluate and manage your budget consumption effectively.
• • Analyze budget consumption from various perspectives, including Month-to-Date, Year-to-Date, Actual figures, and comparisons to the Budget and Last Year.
• • View budget consumption in a tabular format for detailed analysis and insights.

4. Insurance

Insurance companies can leverage Tableau accelerators to analyse claims data, detect fraud, and monitor policy performance.

An example of an insurance accelerator is provided below:

a. Insurance Claims

With this Tableau Accelerator, you can:

• • Assess your performance in handling claims.
• • Identify the most impactful open claims for targeted action.
• • Identify the most effective agents in claims management.
• • Improve the effectiveness of your claims process.
• • Drill down to the specific claim level within your Claim Application and take immediate actions for enhanced efficiency and resolution.

5. Marketing

In the marketing sector, these accelerators assist in analysing trends, identifying growth opportunities, and optimising pricing and product strategies.

An example of an Marketing Accelerator:

a. Email Marketing Campaigns

With this Tableau Accelerator, you can:

• • Assess and enhance the efficiency of your email marketing campaigns.
• • Identify the most impactful campaigns based on key metrics and performance indicators.
• • Conduct an audit of campaign optimisation results over time, enabling data-driven improvements and informed decision-making.

6. Public Sector

Public sector organisations can use Tableau accelerators to monitor government initiatives, improve public service delivery, and track budget allocation. Retail businesses can benefit from analysing sales data, optimising inventory management, and enhancing customer experience.

An example of an Public Sector Accelerator:

a. Emergency Cells

With this Tableau Accelerator, you can:

• • Assess and improve the efficiency of handling emergency calls.
• • Enhance citizen service across different areas.
• • Optimise resource allocation to areas with the greatest need.
• • Adapt staffing levels to accommodate activity peaks and ensure an effective emergency response.

7. Retail

Retail businesses can benefit from Tableau accelerators to analyse sales data, optimise inventory management, and enhance customer experience.

An example of a retail accelerator:

a. Salesforce Data Cloud - Retail Sales by Tableau

This Tableau Accelerator enables you to:

• • Assess network performance and drive sales growth.
• • Predict sales evolution and optimise product mix.
• • Identify emerging/declining products and pinpoint stores in need of assistance.
• • Learn from top-performing stores and identify sales drivers.
• • Dive into detailed insights at the store, product line, and product levels. Watch the demo video to see it in action.

8. Telecommunications

Telecommunications companies can leverage accelerators to analyse network performance and improve customer satisfaction. Supply chain and manufacturing organisations can optimize operations, track production data, and streamline inventory management.

Game Analytics is an example of a telecommunications accelerator:

a. Gaming Analytics by Lovelytics

The Gaming Analytics Accelerator offers performance metrics for your game, integrating game telemetry, usage stats, marketplace data, platform data, and external sources like social media. It provides insights into game-playing patterns, consumption, and revenue. This Accelerator aims to help gaming by:

• • Facilitating the quick and easy acquisition of new customers.
• • Enhancing the gamer experience.
• • Tracking revenue and spending patterns within the game.

9. Supply Chain and Manufacturing

Supply chain and manufacturing organisations can optimise operations, track production data, and streamline inventory management.

a. Occupational Health and Safety by Tableau

With this Tableau Accelerator, you can:

• • Assess and improve employee health in the workplace.
• • Identify safety hazards, risks, and areas of concern.
• • Reduce and prevent injuries, sickness, and accidents.
• • Strive towards the goal of achieving Zero Harm and compliance with industry standards.

10. Energy

Accelerators help monitor energy consumption, optimise resource usage, and track environmental impact in the energy sector.

Two examples of accelerators of the energy sector are given below:

a. Power Grid Connections by Tableau

With this Tableau Accelerator, you can:

• • Assess and enhance your ability to handle Power Grid connection requests.
• • Evaluate the level of service you deliver to customers.
• • Identify priority requests to handle first for efficient resource allocation.
• • Focus your efforts on areas that require immediate attention and improvement.

b. Risk Register Accelerator

The Risk Register Accelerator by Tableau enables you to:

• • Assess your current exposure to risks.
• • Monitor and prioritise risks, focusing on key areas.
• • Evaluate the effectiveness of your risk mitigation and elimination efforts.

Beinex+ Tableau Partnership

Beinex, a premier Tableau partner, provide sustainable analytics solutions to organisations and help to build superior data visual analytics capabilities internally through our bespoke training programs. Our team of Tableau-certified consultants are real-life Tableau business users passionate about Tableau and delivering a world-class experience. Connect with us for a Tableau free trial.