Needing Data Insights to Forecast and Adapt

A company we’ll call TeraDebit needed an analytics platform that could scale with its growing data, and handle data ingestion and transformation processes. Their key objective was to provide a comprehensive business intelligence capability for portfolio leaders to evaluate and compare program performance using on standard KPIs.

A major financial services corporation, TeraDebit’s primary business is to process payments between the merchant banks and other debit card issuers, had partnered with various financial institutions, governments, and NGOs to leverage its core digital technologies. Its hope was to advance agriculture, transform informal to formal financial distributions channels, and increase the reach of health services by providing visibility into the overall value chain.

TeraDebit was seeking to use analytics to foresee and adapt changing customer service expectations and need. However, TeraDebit’s heavy reliance on the merchants and banks to share information limited its capacity to generate actionable insights. Their existing analytics process was not robust or scalable and was therefore unable to support their external reporting needs.

Like many companies undertaking digitalization and business intelligence initiatives, TeraDebit found the time-consuming process required to gain insights prohibitive. Additionally, an incomplete and inconsistent view of data/insights made results prone to manual errors, which could impact the client’s reputation.

Business Challenges and Our Approach

To summarize, we validated the client’s issues and challenges as:

  • The existing analytics process was slow, not robust, and not scalable.

  • There was little to no view of data. Insights were inconsistent and prone to manual errors.

  • The existing platform couldn’t support external reporting needs nor accommodate projected growth.

  • The client was dependent on merchants and banks for data, which further slowed insights.

After a thorough analysis of the client’s existing analytics platform, we shared our perspective on Azure solutions and recommended Azure Data Lake Analytics as one of the options best-suited to the client’s needs. Working within a tight timeline requirement, we started by moving the client’s on-premise data using ADF V2 to Azure Data Lake Storage. Our specialists identified best-in class tools in the Azure environment for the extract, transform, and load (ETL) operations.

For a powerful and all-encompassing view of the actionable insights generated, we rewrote canned reports using Power BI and further developed a user portal using MS.Net and Angular.js. These tools helped render the Power BI reports and enabled the client to have a clear and transparent view of key performance indicators based on the user role access.

Tools & Technology Stack

Tools and Technology Stack

To make the client’s analytics process robust, we leveraged Azure’s Databricks service to perform advanced analytics and ad-hoc querying. We also introduced Azure AD service with service principal multi-factor authentication and database authorization to make the complete process secure.

To achieve an end-to-end automated build and deployment process, we implemented Azure DevOps, creating a CI/CD pipeline. Finally, to enable an “always-on” service, we used Azure’s monitoring service to monitor the service and infrastructure health and availability.

Transformational Effects

Our innovative approaches yielded tremendously positive results. Our solution included an end-end automated deployment process leveraging DevOps, which increased the frequency of the data availability to business and enabled data consistency and removal of manual errors during key sections of the data flow.

Our comprehensive data security framework leveraged cloud-based encryption techniques to secure the PII and other sensitive data using different levels of user access roles. The client’s users are now able to quickly generate actionable insights in real-time using PowerBI.

Implementing a data lake with Azure Analytics was unique and instrumental in engaging the client’s business throughout the entire journey of solution design and build. The client has realized far better performance results and their analytics platform’s robust scalability.

The Trianz Difference

Trianz enables digital transformations through effective strategies and excellence in execution. Collaborating with business and technology leaders, we help formulate and execute operational strategies to achieve intended business outcomes by bringing the best of consulting, technology experiences and execution models.

Powered by knowledge, research, and perspectives, we enable clients to transform their business ecosystems and achieve superior performance by leveraging infrastructure, cloud, analytics, digital, and security paradigms.

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