Data Engineering and Machine Learning Operations are tightly coupled areas of expertise that are an integral part of OpsGuru’s core competencies.

We support companies by helping them to create exceptional products and equip them to make informed business decisions by harnessing the value of their data.

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Real-time Analytics

Stream processing enables organizations to gain real-time insights and respond to real-time events and/or trends efficiently. Typical use cases for stream processing include IoT, stock markets, log collection and analysis, transaction fraud detection and more.


OpsGuru's Big Data experts have helped web-scale companies efficiently process millions of events per second leveraging open source projects such as Spark, Flink and Kafka as well as vendor solutions such as Amazon Kinesis and Google DataFlow. Such robust, secure and cost-efficient ingestion and real-time stream processing pipelines can success the most demanding environments and SLA's. 

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Enterprise Data Lakes

Enterprises and corporations are constantly on the lookout to take advantage of their existing data to drive better business decisions and minimizing costs. Data lake is a preferred choice over traditional data warehouses: by decoupling storage and compute you create a powerful store and processing environment to support structured, semi-structured and unstructured data. Data lake also minimizes data movement and data duplication in multiple stores by leveraging a shared data catalogue.

However, Data Lake deployment is not always straightforward. Since the data now resides in one location and is potentially accessible by a large number of services, it is necessary to take factors like scalability, security and cost-efficiency into account.

OpsGuru's Big Data experts can help you architect and deploy a scalable, secure, fully compliant and cost-effective data lake on a variety of public and private clouds.

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Data Stores

OpsGuru's experts specialise in schema design, performance tuning, disaster recovery strategies as well as security and compliance for multiple industries.

Our Data Stores include:

  • Sub-millisecond OLTP systems like HBase, Cassandra or DynamoDB

  • Petabyte scale OLAP data-warehouses such as Redshift Spectrum

  • Relational databases and web-scale NoSQL databases

Our data engineers help architect, build and operate scalable, performant, compliant and highly available data solutions for the strictest SLA’s.

ML Ops

Machine Learning (ML) algorithms assist companies to make informed business decisions by analysing past data and producing accurate predictions.


ML-based systems in production have extremely subtle properties that are different from traditional software systems, due to the fact that their outputs have more complex behaviours compared to typical software components.

This complexity makes the management of ML systems trickier than the management of traditional, modularized software systems.

OpsGuru helps our customers focus on business logic rather than operations; handling the necessary data preparation tasks, as well as offering a robust and battle-tested CI/CD process optimised for ML model serving and A/B model testing.

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