Crafting Solutions for Your Success
Our Projects
At Analytix Power, our dedicated team of experts leverages technical prowess, deep industry insights, and a customer-focused mindset to provide cutting-edge data solutions. Our mission is to enable organizations to harness the transformative potential of their data, gain invaluable insights, and make well-informed decisions that foster business success in today’s data-driven landscape.
Empowering Solutions for Your Succes
Our Projects
At Analytix Power, our dedicated team of experts leverages technical prowess, deep industry insights, and a customer-focused mindset to provide cutting-edge data solutions. Our mission is to enable organizations to harness the transformative potential of their data, gain invaluable insights, and make well-informed decisions that foster business success in today’s data-driven landscape.
Wanting to access real-time insights, increase efficiencies, and optimize processes, NN Bank embarked on a journey to transform into a data-driven digital retail bank. The key to unlocking this goal was a state-of-the-art data platform capable of delivering high-quality, well-governed, easily accessible, cost-efficient, and secure data products. However, like many large organizations that work with substantial quantities of data, they needed to navigate complex data silos.
Analytix Power Xprts collaborated with NN Bank to craft a data strategy, outlining the ideal tools, technologies, and use cases to meet their objectives. NN Bank opted for Microsoft Azure as the cloud provider and adopted a data mesh architecture framework. This approach empowered different sub-units within NN Bank to establish individual data lakes, each responsible for their own data ingestion, cleaning, and production. Throughout the implementation, our XPrts fostered a data culture, equipping NN Bank with expertise for maintenance and scalability.
- Microsoft Azure as the cloud platform
- Azure Data Factory as an orchestration tool
- Databricks as a distributed data processing platform
- ADLS Gen2 as a data lake storage
- Great Expectations as a Data Quality automation tool
- Python as a programming language
- Terraform as Infrastructure as Code tool
- Azure Key Vault as a secure secrets storage tool
Recognizing their rapidly growing data volume, Translink decided to implement a more modern and scalable data platform. This platform needed to be able to handle both streaming and batch data. In addition, it needed to be cost-efficient, fast, secure, accessible, and scalable to petabytes of data. Such an endeavor is ambitious for even the most skilled data engineers.
Translink worked alongside an XPrt from Analytix Power to select a cloud platform and architecture suitable to handle and process massive amounts of data. Together, they implemented a new cloud data platform backed by Microsoft Azure using Azure native data services. A data lakehouse architecture supported this. With this new modernized platform and enhanced processing capabilities, Translink is now able to stay on top of their data volume and better serve customers.
- Microsoft Azure as the cloud platform
- Azure Event Hubs as a streaming tool
- Azure Synapse Analytics with Spark as data processing platform
- ADLS Gen2 as storage
- Python as a programming language
As an organization with valuable customer data scattered across various sources, Fuga wanted to centralize to leverage these insights more effectively. Doing so would allow them to understand customer behavior better and identify tactics to attract more customers. They sought to implement a data ingestion framework capable of importing assorted data into a single, cloud-based data warehouse on a scheduled basis. They also wanted to be able to run data ingestion logic and design their workflow without building a new infrastructure for each use case.
Fuga reached out to Analytix Power to help them achieve this goal simply and cost-effectively. Our XPrts introduced Apache Airflow as the workflow engine, but tested it on one use case before scaling to ensure it would function as expected. Once it did, it was applied to all use cases. As a result of this custom, scalable framework, Fuga saved a great deal of time and money. They have become a data-driven organization capable of leveraging advanced analytics and insights to understand, attract, and retain customers.
- Docker as containerization platform
- Python as programming languages
- Airflow as open-source platform
Mortgages, a domain within NN Bank, wanted to increase the speed of its mortgage application processes to improve the experience of eager customers. However, this goal would require a reliable, real-time flow of data, enhanced by advanced analytics and AI. This multi-step process is highly complex and is best executed by a subject matter expert in data engineering.
The Mortgages team and our XPrts set out to implement event-driven architecture, increasing the speed of the mortgage application process from beginning to end. Our teams collaborated to build real-time data pipelines that would feed into a process mining tool, turning event data from the mortgage application process into insights and actions continuously. As a result, applications move through the process at a significantly quicker rate, improving customer satisfaction overall.
- Confluent Platform as the data streaming Platform
- Kafka as the data streaming middleware
- Kafka Connect as the data streaming integration framework
- Neo4J as a realtime customer 360 database
- Celonis as a process mining tool
- Salesforce as a CRM system
- AWS EventBridge as a serverless event bus
Achmea’s HR Analytics team sought to modernize and migrate from a legacy system to the cloud. For this, they would need a new and improved data platform that was cost-efficient, fast, scalable, and would allow for the easy expansion of data available to the HR Analytics team. Finally, it would need to integrate with existing reporting and visualization tools.
Achmea identified Microsoft Azure as the cloud provider that best aligned with their use cases along with a medallion architecture. With the support of an Analytix Power Xprt, they implemented the gold layer of the medallion architecture. This enabled complex transformations to be made and stored independent of the data pre-processing. The HR Analytics team now has easy access to the data they need, when they need it.
- Microsoft Azure as the cloud platform
- Azure Synapse Analytics as an orchestration and distributed data processing platform
- ADLS Gen2 as a data lake storage
- Python as a programming language
The ABN AMRO Mortgages team struggled to get access to the data they needed when needed, so they wanted to design and implement a modern data platform that could process and deliver data quickly and cost-effectively. In addition, they found that data engineers across the company had different ways of working, which reduced overall efficiency. To remedy this, they sought to create a library containing standardized functionalities to decrease time-to-market.
To execute their data platform vision, the ABN AMRO Mortgages team worked alongside Analytix Power to implement a Data Mesh based on the Lakehouse Architecture on Microsoft Azure. To standardize data engineer ways of working, Analytix Power assisted with developing a library of functionalities for core tasks. This now serves as a single source of truth for engineers across ABN AMRO to work from, improving processes and operations overall.
- Microsoft Azure as the cloud platform
- Apache Airflow as an orchestration tool
- Databricks as a distributed data processing platform
- ADLS Gen2 as a data lake storage
- Azure Functions as an event-driven, serverless computing platform
- Event Hub as an event ingestion service
- Azure Key Vault is a secure secrets storage tool
- Python as a programming language
As an organization that prioritizes the experience of its customers, NN Bank sought to provide website users with timely and relevant insights and recommendations based on their preferences. To achieve this, they would need to ensure their data platform was capable of producing real-time data products based on the unique behavior of each user. This type of programming is incredibly complex and requires a combination of a highly advanced skillset and the right tools.
NN Bank enlisted the support of Analytix Power to make this vision a reality. We worked with our partner, Confluent, to introduce event-driven architecture and streaming analytics. Event-driven architecture uses events to trigger and communicate between services, ensuring that each customer receives insights and recommendations based on their real-time behavior and preferences as they navigate NN Bank’s website. NN Bank can now reach its customers in a more targeted, personalized way.
- Confluent Platform is used as Data Streaming Platform
- Kafka is used as Data Streaming middleware
- Kafka Connect as Data Streaming integration framework
- KSQL DB as Data Stream processing engine
- Schema Registry as schema repository
- Neo4J as realtime customer 360 database
- Adobe Experience Cloud as Customer Engagement Platform
- AWS as Cloud service provider
- Amazon Elastic Kubernetes Service as container platform
- Microsoft Azure as cloud service provider
- Personetics as Personal Financial Management tool
- MongoDB as operational data store
- AWS Lambda as serverless event driven compute engine for implementing microservices
Making informed decisions based on reliable and well-governed data is more critical than ever. Discover how we can assist in achieving this goal.