Data Platform Modernization

A well-architected data platform makes data more readily accessible, reliable and compliant -
empowering critical, real-time business decisions.

Modernize Your Data Platform

Data Platform Specialists

Data platform modernization is the process of restructuring code, infrastructure, microservices and database technologies to improve the design of the solution. In most cases, modernization does not change core functionality and preserves original behavior.

Modernize with Us Today

Modernizing solutions on the cloud generally refers to adopting cloud-native services in order to leverage all aspects of the cloud computing model. Often, organizations don't have a firm grasp of all the technologies available and how to implement a cloud-native solution.

Global Development Flexibility with On-Demand Delivery
Cost Savings with Pay-Per-Use Model Elasticity and Scalability
Fault-Tolerant Reliability Ease of Use with Managed Services

Depending on the organization's current cloud footprint, modernization can be completed via a stepped or all-in strategy. A stepped approach is generally done with an organization's initial transition into the cloud. It requires slight changes to the data platform while underlying technology such as security, networking and identification management are switched to cloud-native solutions.

Data System Refactoring - On-premise database technologies are assessed and evaluated for modernization. As we modernize your solution it's imperative that the correct cloud services and technologies are selected. Factors that drive which cloud services are used are:

Velocity and Volume of data
Elasticity and Scalability- building solutions for variable workloads
Loosening tightly coupled solutions
High-Availability and Disaster Recovery
Future data needs of the organization

Application Refactoring - In our experience, modernization of the data platform's front-end application usually consists of moving to cloud-native serverless solutions and containerization to efficiently and effectively scale to meet the data workload.

Looking into the Future of your data - After a data platform solution has been successfully modernized to the cloud, new ideas and ways to use the data emerge due to the flexibility and agility offered in the cloud. Customers then seek new ways to use their data and want to create new insights and revenue streams. New functionality and features can include:

Detect Fraudulent Activity Automatically detect potentially fraudulent credit card transactions by processing transactions through a machine learning model.

Deploy a Data Lake Build a framework that automatically deploys a data lake with consoles capable of cataloging, searching and visualizing data sets.

Predict Customer Churn Deploy a solution that automates the collection of customer data, predicts customer churn using ML, and maintains a tailored audience segment for messaging.

Real-Time IoT Device Monitoring Stream real-time IoT data to dashboards for user monitoring. Send notifications out to a tailored audience based on events.

Media Analysis Solution Automatically extract valuable information from your media files using AI.

Modernize Your Data Platform

Thanks! We'll contact you soon.


Database Migration Case Studies

Database Modernization to AWS
Case Study: Acoustic

Acoustic's Journey from IBM DB2 to AWS Redshift

Our customer's journey to an all-in adoption of cloud database computing.

Case Study: Canadian Financial Institution

Modernizing ETL business process from Informatica to AWS Glue

Our customer's journey out of expensvive Informatica ETL software and onto AWS Glue and other AWS Services.

Database Migration to AWS
Infra as Code Automation
Case Study: Acoustic

Automate the creation of a DB2 HADR Cluster in AWS

Hear how we tackled migrating over 300 DB2 servers to AWS with infrastructure as code automation scripts.

Case Study: Acoustic

Acoustic's DB2 Database Journey to AWS

Hear how we lift & shifted over 300 DB2 database systems to AWS in 8 months.

Database Modernization to AWS
Case Study: Acoustic

Acoustic's journey from DB2 DB to Aurora PostgreSQL

Hear our customer's database modernizastion journey to AWS Aurora PostgreSQL and other AWS Services.

"Data driven organizations are 19X more likely to be profitiable"

- McKinsey & Company

Modernization to GCP
Case Study: Canadian Financial Institution

Modernizing On-premise Hadoop to GCP

A technical guide on what GCP services to pick and why

Case Study: Travel Bidding Website

Oracle Migration to GCP CLoudSQL

Our strategy on how we moved Travel Bidding Website's Oracle data systems to GCP CloudSQL using Striim