Data Mesh Services

Accelerate and Enhance Analytical Capability Via Data Mesh

In today’s hyper-competitive environment, companies are increasingly opting for data lakes with real-time stream processing and data availability. Organizations are opting for this with the intent to ingest, enrich, transform, and serve data to a centralized platform. However, for a majority of organizations this architecture has a few shortcomings:

• Teams have less control over enormous sets of distributed data via a central ETL pipeline.
• Organizations today generate new, vast sets of data and this requires different types of transformation for different data use cases. This scenario puts huge pressure on the central platform.

Chaotic lakes of data result in impatient and disconnected data consumers and backlogged data teams. Our data mesh services offer domains or business areas with the capability to perform enhanced analytics without the need of a centralized data lake. This system puts control in the hands of your domain teams, making them responsible to manage their data quality and pipelines.

Effective, Efficient Delivery of Impactful Data

Data is a simple yet complex aspect of businesses today. Businesses are often challenged with issues like: real-time access to data across their enterprise (some on-prem and some in a multi-cloud environment), application services not able to query the right data for analytical needs, the high costs of creating a centralized data lake and the dilution in ownership of data.

Olympic’s data mesh services will assist you in overcoming these pain points effectively and efficiently. Our data mesh services:

• Will help to connect to your data sources wherever they are (on-prem or multi-cloud) in order to overcome your data complexities.
• Offer an accelerated solution to build business intelligence analytics without the need to move to a centralized data lake; because importing data to and from your data warehouse can often be a costly affair.
• Assist you in navigating seamlessly within the data loop and its varied aspects, from information to action.
• Effectively implement an enterprise data analytics platform in months instead of years.