Zensar Technologies Case Studies Revamping the Data Lake of a Securities Company for Reliability and Scalability

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	Revamping the Data Lake of a Securities Company for Reliability and Scalability Zensar Technologies

Revamping the Data Lake of a Securities Company for Reliability and Scalability

Zensar Technologies

Technology Category	Application Infrastructure & Middleware - Database Management & Storage Infrastructure as a Service (IaaS) - Cloud Storage Services
Applicable Industries	Construction & Infrastructure Retail
Applicable Functions	Maintenance
Use Cases	Construction Management Infrastructure Inspection
Challenge	Our client, a South African company dealing with the settlement of various securities, had invested in an on-premises data lake as a single, reliable source for data-driven decision making. Despite significant investment, the client was unable to achieve the desired agility and scalability. The data lake’s infrastructure presented several challenges including inability to scale, high infrastructure and maintenance costs, and lack of cloud-based computing. Its monolithic architecture was unable to handle the client’s increasing data storage and analytics needs. The absence of cloud-based services resulted in underutilization of the data lake by business users. It was inaccessible by many, lacked real-time services, and was regarded as an unreliable source, leading to significant revenue leakages. Read More
About Customer	The client is a South African company that handles the settlement of various securities such as equities and bonds, as well as a range of derivatives including warrants, retail notes, and tracker funds. The client had invested in an on-premises data lake as a single, reliable source for data-driven decision making. However, despite significant investment, the client was unable to achieve the desired agility and scalability from the data lake. The client faced several challenges due to the nature of the data lake’s infrastructure, including inability to scale, high infrastructure and maintenance costs, and lack of cloud-based computing. Read More
Customer Name	Not disclosed Read More
Solution	As the client’s technology partner, we began with a current state assessment to understand the aforementioned roadblocks. After identifying all the pain points, we collaborated with the client to lay out a long-term analytics roadmap for them to become a data-driven organization. The data lake was migrated to MS Azure to implement this data roadmap. To ensure that the long-term solution would cope with the organization’s exponential data growth, we designed the Azure Analytics architecture in which the data warehouse, data pipelines, ETL jobs, and 60+ reports and dashboards were created. To ensure full utilization of the cloud infrastructure, we implemented the relevant process flows and improvements to the end-user experience so that the user would only be presented with relevant data. Read More Log in to view content
Contents

Technology Category

Application Infrastructure & Middleware - Database Management & Storage

Infrastructure as a Service (IaaS) - Cloud Storage Services

Applicable Industries

Construction & Infrastructure

Retail

Applicable Functions

Maintenance

Use Cases

Construction Management

Infrastructure Inspection

Challenge

Our client, a South African company dealing with the settlement of various securities, had invested in an on-premises data lake as a single, reliable source for data-driven decision making. Despite significant investment, the client was unable to achieve the desired agility and scalability. The data lake’s infrastructure presented several challenges including inability to scale, high infrastructure and maintenance costs, and lack of cloud-based computing. Its monolithic architecture was unable to handle the client’s increasing data storage and analytics needs. The absence of cloud-based services resulted in underutilization of the data lake by business users. It was inaccessible by many, lacked real-time services, and was regarded as an unreliable source, leading to significant revenue leakages.

About Customer

The client is a South African company that handles the settlement of various securities such as equities and bonds, as well as a range of derivatives including warrants, retail notes, and tracker funds. The client had invested in an on-premises data lake as a single, reliable source for data-driven decision making. However, despite significant investment, the client was unable to achieve the desired agility and scalability from the data lake. The client faced several challenges due to the nature of the data lake’s infrastructure, including inability to scale, high infrastructure and maintenance costs, and lack of cloud-based computing.

Customer Name

Not disclosed

Solution

As the client’s technology partner, we began with a current state assessment to understand the aforementioned roadblocks. After identifying all the pain points, we collaborated with the client to lay out a long-term analytics roadmap for them to become a data-driven organization. The data lake was migrated to MS Azure to implement this data roadmap. To ensure that the long-term solution would cope with the organization’s exponential data growth, we designed the Azure Analytics architecture in which the data warehouse, data pipelines, ETL jobs, and 60+ reports and dashboards were created. To ensure full utilization of the cloud infrastructure, we implemented the relevant process flows and improvements to the end-user experience so that the user would only be presented with relevant data.

Impact #1	The migration of the data lake to MS Azure and the implementation of the Azure Analytics architecture resulted in significant improvements in the client's operations. The client was able to become a data-driven organization, with the ability to handle exponential data growth. The cloud infrastructure was fully utilized, with relevant process flows and improvements to the end-user experience. This resulted in users being presented with only relevant data, enhancing the efficiency of data-driven decision making. The solution also improved future scalability, enabling faster sharing of insights with internal and external stakeholders.

Impact #1

The migration of the data lake to MS Azure and the implementation of the Azure Analytics architecture resulted in significant improvements in the client's operations. The client was able to become a data-driven organization, with the ability to handle exponential data growth. The cloud infrastructure was fully utilized, with relevant process flows and improvements to the end-user experience. This resulted in users being presented with only relevant data, enhancing the efficiency of data-driven decision making. The solution also improved future scalability, enabling faster sharing of insights with internal and external stakeholders.

Benefit #1	Saved ~$100k by eliminating fee leakage within 2 months of implementation
Benefit #2	Reduced TCO by ~50%
Benefit #3	Eliminated redundant data and reduced storage cost by 80%

Benefit #1

Saved ~$100k by eliminating fee leakage within 2 months of implementation

Benefit #2

Reduced TCO by ~50%

Benefit #3

Eliminated redundant data and reduced storage cost by 80%

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Overview

Revamping the Data Lake of a Securities Company for Reliability and Scalability

Operational Impact

Quantitative Benefit