DataOps Services

Manage enterprise data operations with robust DataOps expertise

With Sigmoid’s DataOps services, organize your data efficiently by creating a DataOps pipeline and keep it business-ready throughout the entire data lifecycle. We ensure a continuous development, integration, testing, deployment and monitoring of enterprise data operations. Our DataOps expertise carries data automation, data governance and data democratization while providing data lifecycle management.

Our 7C’s Approach

Process

Standardise

  • Monitor/analyze system metrics
  • Data lifecycle management with 24/7 support
  • Setup alert notifications and standard scripts

Improve

  • Implement new tools
  • Implement automation
  • Tweak performance Issues

Innovate

  • Build solution based on business needs
  • Automate at scale and speed up deployment
  • Enforce test and quality

Process

Standardize

Monitor/analyze system metrics

Data lifecycle management with 24/7 support

Setup alert notifications and standard scripts

Improve

Implement new tools

Implement automation

Tweak performance Issues

Innovate

Build solution based on business needs

Automate at scale and speed up deployment

Enforce test and quality

Our DataOps Expertise

Data Automation

Handle Petabytes of real time data and identify/ eradicate manual intervention

Data Governance

Prompt notification and escalation of anomalies are reported by engineers through

Communication

Automate and integrate; Escalate in multiple channels: Slack/Hangout/Email/PagerDuty calls

Democratize Data

Integrate code without refactoring, resulting in productivity improvements

Monitoring

Monitor and perform DataOps pipelines with in-depth RCA and CAPA

DMAIC Process

Perform process improvements through Definition/ Measure/ Analyse/ Improve/ Control

24/7 Support

Get continuous support and maximum up-time from our dedicated pool of engineers

Cross Industry Competence

Delivering productivity improvements across Retail, CPG, BFSI, Hi-tech, etc.

100% Tech Stack Coverage

We cover technologies across the data spectrum to cater to current as well as future needs.

Success Story

Improved Data Pipeline Availability and Stability 99% uptime delivered | 60% reduction in operations cost | 55% reduction in new incidents

Tech Stack

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Spark is a general-purpose distributed data processing engine designed for fast computation. The main feature of Spark is its in-memory cluster computing that increases the processing speed of an application. It supports workloads such as batch applications, iterative algorithms, interactive queries and streaming.

Need for effective Log management systems – Comparing Splunk & Elastic Search

Continuous integration and Continuous Deployment have increasingly shortened the time taken to build applications that need frequent changes, while still maintaining a reliable delivery process.

Learn more about the data engineering services

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Cloud Migration