The customer’s goal was to develop an enterprise cloud foundation which could enable cost savings, faster delivery and enhanced capability of its IT services.
Innovation is built into the customer’s culture, however, as with many companies of its size and heritage, development cycles are long and change in IT is slow and difficult terrain to manage.
The customer wanted a cloud-native partner that would listen to its requirements, build a foundation that can be built on for years to come and help the business navigate and adjust with the changes.
They wanted to focus on a series of “game changers” in governance, organization, operations, billing and recovery, identity and security, connectivity and to automate everything.
Cloudreach was brought in to help the company navigate four key “Epics”.
- Build a roadmap – A long-term plan for cloud adoption.
- Build a enterprise cloud foundation – To enable proof of value system and lay out the businesses foundation for building the cloud.
- Proof of value – Show the benefits of cloud-native big data and analytics environment.
- Develop processes- Work on a more agile and nimble model for our business
The customer selected AWS because it was impressed with the their products and services offering and the platform’s position in the market.
After working closely with the customer’s in-house IT team to build a roadmap, Cloudreach held workshops with a variety of stakeholders from across the business to develop a high-level design and governance structure that was tailor-made for their businesses. Using industry-standard IaaC (Infrastructure as a Code) tools, Cloudreach developed a multi-account AWS landing zone that provided security segmentation across business units and environments. In addition, Cloudreach developed a short-term and long-term network design to integrate the AWS environments with the company’s existing data center. As part of the foundational build, Cloudreach built and demonstrated cloud-native tools like centralized logging, governance compliance, and security controls. The result was an integrated cloud landing zone that was ready for the customer’s various business lines to start using.
In the next phase, Cloudreach helped the customer native build POVs which enabled analytics processes on top of a foundational data lake/data catalog. As a part of the data lake build, Cloudreach helped the customer transition to a more efficient and effective data engineering process through AWS. Cloudreach built a data lake and data warehouse on AWS for the customer’s TGV Smart Manufacturing Data and Predictive Analytics and GSM Cost and Spend Analysis team. Through a series of workshop sessions, Cloudreach was able to define a solution that would meet the needs of each team. They also demonstrated the ability to ingest and transform data, centralized a data catalog for searching and finding data, increased end-user benefits for data visualization via BI tools, and helped provide a clearer understanding of data processing and lineage of data flows from source to end consumption. All this was achieved with little or no disruption to the existing data flow system
While working on the POV, there were some last minute requirement changes where the end user wanted additional data manipulation and visualization to be performed. The customer viewed it as critical to evaluate the performance of AWS. Within a limited time frame, the Cloudreach team was able to come up with a solution to work around the limitation of AWS Glue and demonstrate the data manipulation with the help of Lambda scripts and visualization through Zeppelin BI, a tool that the customer was familiar with.
The customer also wanted a data lake foundation that would provide a clearer understanding of the data processing and lineage of data flow. Cloudreach developed a solution that showed the lineage of data flow from source to target, including the data transformation.
Cloudreach ensured good quality work within the timeline, was always one step ahead in understanding the customer’s needs, and provided constant support for the team.
Improved and automated file conversion process- Cloudreach implemented transformation using AWS Glue which automated the file conversion process.
Increased end-user benefits with a data warehouse to connect various BI tools– Cloudreach implemented Redshift data warehouse which would store all the processed data and can be easily connected to by the BI tools (Zeppelin, PowerBI) being used by the customer.
Reduced the cost of processing and consuming data -Cloudreach demonstrated the cost benefits of S3 and Redshift. Also, time benefits when resizing of redshift cluster took minutes compared to months in on-prem.
Simpler data management and consumption- Cloudreach demonstrated simpler and enhanced transformations and consumption capabilities using AWS Glue, Redshift, and S3, pulling in data from the existing on-prem system with no disruption to the existing data flow system, and proved similar end-user benefits on AWS.
Realized benefits of building a data lake – Through the data lake POV we helped understand the benefit of building data lake on AWS and its enhanced consumption capabilities. It helped the customer understand how AWS would help simplify their current data flow across the systems and also provide enhanced data analytics.
About Multinational Technology Company
The customer is a US-based multinational technology company which has been engineering and manufacturing life-changing innovations for over 160 years. Primarily focusing on solutions for industrial and scientific applications, the company maintains an extensive product portfolio with a focus on high-quality, precision, and innovation.
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