Are you ready to make a leap into the data-driven future with Fyrefuse but need help getting your boss on board? Here are a few business benefits of DataOps to share with your company’s non-technical decision-makers.
If you are familiar with DataOps, you probably know that the advantages this approach provides in terms of data collaboration and automation are hard to underestimate. Yet, it can be challenging to communicate these benefits to non-technical decision-makers in your company. Below you can find a brief introduction to DataOps and Fyrefuse, followed by a handful of business benefits you can share with your boss or managers to get them excited about Fyrefuse.
According to Gartner, DataOps is one of the hottest trends of 2021 and it’s defined as ”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.”
Specifically, DataOps, or data operations, focuses on overcoming a collective set of challenges that most organizations, sooner or later, find on their roadmap to become data-driven.
It cultivates data management practices to improve the speed and accuracy of analytics, including data access, quality control, data governance, automation and integration.
If you’re interested in a deeper understanding of DataOps take a look at our previous article on our blog.
Fyrefuse is an end-to-end DataOps platform that automates and connects stakeholders, tools and policies to improve data life-cycle in a Big data organisation. Main features include data discovery and exploration, data pipelines, team management, collaboration, rules and governance.
It offers the possibility to design, launch and schedule reusable data ingestion pipelines with zero coding swiftly. The platform provides real time monitoring of multiple concurrent executions and totally eliminates undocumented data flows.
What are the Business Gains in case your company decides to adopt Fyrefuse?
Fyrefuse connects data from different sources or systems and helps reduce the time spent searching for the right data, so IT can adapt at the speed of business.
It provides the possibility for timelier and more accurate reporting as analysts can dedicate their time to generating insights without delays and workflow mialignments. Each pipeline is documented in detail through auditable logs and the possibility of downloading a complementary rudder file. In this way, Fyrefuse reduces cycle time to publish new insights from months/weeks to one day.
Leave more time for your developers to focus on more complex tasks and use Fyrefuse’s automated, reusable, and constantly monitored pipelines. Fyrefuse reduces troubleshooting time and costs in modern business environments and eliminates engineering dependency with codeless setup and monitoring.
Data engineers can also drive value rather than building pipelines and fixing issues.
Moreover, collaboration and communication tools allow all the stakeholders to speak a common language and improve data literacy among business users.
Fyrefuse is built using best-of-breed open source technologies such as Scala, Akka, Kafka and Lagom and it is powered by a user-friendly portal that leverages Python, Django and Angular 8. Based on a microservice architecture, Fyrefuse is deployed on Kubernetes to ensure continuous data delivery both on-prem or in cloud.
This setting allows for an easy deployment into dev and staging environments in an automated manner, while streamlining monitoring and reporting through transparent Data Operations dashboards.
Fyrefuse’s ready-to-use prebuilt connectors and scheduling techniques minimize downtime. Moreover, data sources can be connected in seconds through autodiscovery or schema upload in an intuitive and friendly way. To do this, Fyrefuse reads the schema of a repository and selects all or a share of the available tables to be visualized in the Data Explorer.
Siloed IT Operations, hindered collaboration between data scientists, data owners and data engineers are pushing organisations to rethink the way they handle AI initiatives. Fyrefuse boosts AIOps and makes the process flexible for all the stakeholders with different levels of technical skills.
Fyrefuse connects sandboxes and allows data analysts and scientists to glean more data with automated pipelines and embedded data governance. The time gained from collaboration and Agile data request management can be rather used to improve and monitor the accuracy of the models.
In order to render data visible and available for self-service in a governed way, Fyrefuse allows users to explore metadata in two alternative ways: Business Glossary and Data Catalog. The Business Glossary is a non-technical way of organizing data that enables data scientists to focus just on production and liberate them from engineering dependencies
To conclude, it’s crucial to manage data flows responsibly and in an automated fashion and Fyrefuse helps standardize design patterns, reduce troubleshooting costs and embrace the change that Big data era is facing us.