Zephyrnet Logo

Generative Data Intelligence

Big Data

How AWS helped Altron Group accelerate their vision for optimized customer engagement | Amazon Web Services

Republished By Plato
Republished By Plato

Date:

Views: 73

This is a guest post co-authored by Jacques Steyn, Senior Manager Professional Services at Altron Group.

Altron is a pioneer of providing data-driven solutions for their customers by combining technical expertise with in-depth customer understanding to provide highly differentiated technology solutions. Alongside their partner AWS, they participated in AWS Data-Driven Everything (D2E) workshops and a bespoke AWS Immersion Day workshop that catered to their needs to improve their engagement with their customers.

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. They were able to think big but start small with a working solution involving rich business intelligence (BI) and insights provided to their key business areas.

Data-Driven Everything engagement

Altron has provided information technology services since 1965 across South Africa, the Middle East, and Australia. Although the group saw strong results at 2022-year end, the region continues to experience challenging operating conditions with global supply chains disrupted, electronic component shortages, and scarcity of IT talent.

To reflect the needs of their customers spread across different geographies and industries, Altron has organized their operating model across individual Operating Companies (OpCos). These are run autonomously with different sales teams, creating siloed operations and engagement with customers and making it difficult to have a holistic and unified sales motion.

To succeed further, their vision of data requires it to be accessible and actionable to all, with key roles and responsibilities defined by those who produce and consume data, as shown in the following figure. This allows for transparency, speed to action, and collaboration across the group while enabling the platform team to evangelize the use of data:

Altron engaged with AWS to seek advice on their data strategy and cloud modernization to bring their vision to fruition. The D2E program was selected to help identify the best way to think big but start small by working collaboratively to ideate on the opportunities to build data as a product, particularly focused on federating customer profile data in an agile and scalable approach.

Amazon mechanisms such as Working Backwards were employed to devise the most delightful and meaningful solution and put customers at the heart of the experience. The workshop helped devise the think big solution that starting with the Systems Integration (SI) OpCo as the first flywheel turn would be the best way to start small and prototype the initial data foundation collaboratively with AWS Solutions Architects.

Preparing for an AWS Immersion Day workshop

The typical preparation of an AWS Immersion Day involves identifying examples of common use case patterns and utilizing demonstration data. To maximize its success, the Immersion Day was stretched across multiple days as a hands-on workshop to enable Altron to bring their own data, build a robust data pipeline, and scale their long-term architecture. In addition, AWS and Altron identified and resolved any external dependencies, such as network connectivity to data sources and targets, where Altron was able to put the connectivity to the sources in place.

Identifying key use cases

After a number of preparation meetings to discuss business and technical aspects of the use case, AWS and Altron identified two uses cases to resolve their two business challenges:

  • Business intelligence for business-to-business accounts – Altron wanted to focus on their business-to-business (B2B) accounts and customer data. In particular, they wanted to enable their account managers, sales executives, and analysts to use actual data and facts to get a 360 view of their accounts.
    • Goals – Grow revenue, increase the conversion ratio of opportunities, reduce the average sales cycle, improve the customer renewal rate.
    • Target – Dashboards to be refreshed on a daily basis that would provide insights on sales, gross profit, sales pipelines, and customers.
  • Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.
    • Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Conducting the Immersion Day workshop

Altron set aside 4 days for their Immersion Day, during which time AWS had assigned a dedicated Solutions Architect to work alongside them to build the following prototype architecture:

This solution includes the following components:

  1. AWS Glue is a serverless data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application development. The Altron team created an AWS Glue crawler and configured it to run against Azure SQL to discover its tables. The AWS Glue crawler populates the table definition with its schema in AWS Glue Data Catalog.
  2. This step consists of two components:
    1. A set of AWS Glue PySpark jobs reads the source tables from Azure SQL and outputs the resulting data in the Amazon Simple Storage Service “Raw Zone”. Basic formatting and readability of the data is standardized here. The jobs run on a scheduled basis, according to the upstream data availability (which currently is daily).
    2. Users are able to manually upload reference files (CSV and Excel format) via the Amazon Web Services console directly to the Amazon S3 buckets. Depending on the frequency of upload, the Altron team will consider automated mechanisms and remove manual upload.
  3. The reporting zone is based on a set of Amazon Athena views, which are consumed for BI purposes. The Altron team used Athena to explore the source tables and create the views in SQL language. Depending on the needs, the Altron team will materialize these views or create corresponding AWS Glue jobs.
  4. Athena exposes the content of the reporting zone for consumption.
  5. The content of the reporting zone is ingested via SPICE in Amazon QuickSight. BI users create dashboards and reports in QuickSight. Business users can access QuickSight dashboards from their mobile, thanks to the QuickSight native application, configured to use single sign-on (SSO).
  6. An AWS Step Functions state machine orchestrates the run of the AWS Glue jobs. The Altron team will expand the state machine to include automated refresh of QuickSight SPICE datasets.
  7. To verify the data quality of the sources through statistically-relevant metrics, AWS Glue Data Quality runs data quality tasks on relevant AWS Glue tables. This can be run manually or scheduled via Amazon Eventbridge (Optional).

Generating business outcomes

In 4 days, the Altron SI team left the Immersion Day workshop with the following:

  • A data pipeline ingesting data from 21 sources (SQL tables and files) and combining them into three mastered and harmonized views that are cataloged for Altron’s B2B accounts.
  • A set of QuickSight dashboards to be consumed via browser and mobile.
  • Foundations for a data lake with data governance controls and data quality checks. The datasets used for the workshop originate from different systems; by integrating the datasets during the workshop implementation, the Altron team can have a comprehensive overview of their customers.

Altron’s sales teams are now able to quickly refresh dashboards encompassing previously disparate datasets that are now centralized to get insights about sales pipelines and forecasts on their desktop or mobile. The technical teams are equally adept at adjusting to business needs by autonomously onboarding new data sources and further enriching the user experience and trust in the data.

Conclusion

In this post, we walked you through the journey the Altron team took with AWS. The outcomes to identify the opportunities that were most pressing to Altron, applying a working backward approach and coming up with a best-fit architecture, led to the subsequent AWS Immersion Day to implement a working prototype that helped them become more data-driven.

With their new focus on AWS skills and mechanisms, increasing trust in their internal data, and understanding the importance of driving change in data literacy and mindset, Altron is better set up for success to best serve their customers in the region.

To find out more about how Altron and AWS can help work backward on your data strategy and employ the agile methodologies discussed in this post, check out Data Management. To learn more about how can help you turn your ideas into solutions, visit the D2E website and the series of AWS Immersion Days that you can choose from. For more hands-on bespoke options, contact your AWS Account Manager, who can provide more details.

Special thanks to everyone at Altron Group who helped contribute to the success of the D2E and Build Lab workshops:

  • The Analysts (Liesl Kok, Carmen Kotze)
  • Data Engineers (Banele Ngemntu, James Owen, Andrew Corry, Thembelani Mdlankomo)
  • QuickSight BI Developers (Ricardo De Gavino Dias, Simei Antoniades)
  • Cloud Administrator (Shamiel Galant)

About the authors

Jacques Steyn runs the Altron Data Analytics Professional Services. He has been leading the building of data warehouses and analytic solutions for the past 20 years. In his free time, he spends time with his family, whether it be on the golf , walking in the mountains, or camping in South Africa, Botswana, and Namibia.

Jason Yung is a Principal Analytics Specialist with Amazon Web Services. Working with Senior Executives across the Europe and Asia-Pacific Regions, he helps customers become data-driven by understanding their use cases and articulating business value through Amazon mechanisms. In his free time, he spends time looking after a very active 1-year-old daughter, alongside juggling geeky activities with respectable hobbies such as cooking sub-par food.

Michele Lamarca is a Senior Solutions Architect with Amazon Web Services. He helps architect and run Solutions Accelerators in Europe to enable customers to become hands-on with AWS services and build prototypes quickly to release the value of data in the organization. In his free time, he reads books and tries (hopelessly) to improve his jazz piano skills.

Hamza is a Specialist Solutions Architect with Amazon Web Services. He runs Solutions Accelerators in EMEA regions to help customers accelerate their journey to move from an idea into a solution in production. In his free time, he spends time with his family, meets with friends, swims in the municipal swimming pool, and learns new skills.

spot_img

Latest Intelligence

spot_img

Copyright @ 2024 Plato Technologies Inc.