Data
Howdy, champs!
Data Ops
Our modern practice delivers powerful DevOps benefits. Our approach gives leaders the agility they need to scale or pivot their software quickly to meet constantly changing business demands, freeing your delivery pipeline of silos and out-of-date processes, archaic engineering practices, and inadequate tools.
Data Ops
Data Pipelines
DataOps is a collaborative data management practice, really focused on improving communication, integration, and automation of data flow between managers and consumers of data within an organization.
Cloud storage
DataOps is a data management method that emphasizes communication, collaboration, integration, automation and measurement of cooperation between data engineers, data scientists and other data professionals.
API’s
DataOps is all about bringing together the tools you love, the processes you need and your people, in a single place for better data management within your organization.
01. Real-time and
actionable insights
Increase through agile methodologies, code-free tools, component reuse, collaboration, and analyst self-reliance.
02. Informed and
empowered decisions
The ability to scale the data “production line,” a problem many organizations have difficulty overcoming in a secure, governed, and consumable manner.
03. Drive revenue and
user engagement
Improve the data pipeline output quality to build trust in the data via improved data cleansing, data usability, data completeness, and transparency.
How it works
DataOps applies to the entire data lifecycle from data preparation to reporting and recognizes the interconnected nature of the data analytics team and information technology operations.
Howdy, champs!
The Tableau and Informatica solution
DataOps is an emerging new process in the data analytics world that applies DevOps concepts to data management for analytics. To downstream analytics and data science teams, DataOps promises to deliver the speed, efficiency, quality, and productionizing of data delivery for their analytics needs.
