The Importance of Operationalizing Data Projects: A Role for DataOps and Orchestration
Data has become a critical asset for businesses, with analysts stressing the importance of effectively harnessing this resource. However, it’s often overlooked that many data projects don’t make it to production. In 2016, Gartner predicted that by 2024, organizations lacking a sustainable data and analytics operationalization framework would face significant business disruptions [1]. To navigate this challenge, DataOps comes into play.
Data Operations: Building a Bridge Between DevOps and Business Value
Operationalizing data projects has been vital for organizations in transforming their data deluge into actionable digital strategies [2]. DataOps builds upon the foundation laid by DevOps, enabling seamless collaboration between IT and business teams to deliver high-quality data at speed.
Orchestration: The Backbone of DataOps
To effectively operationalize data projects, good orchestration is essential. Basil Faruqui, Solutions Marketing Director at BMC, explains: “Think about building a data pipeline – whether simple or complex, you have stages like data ingestion, storage, processing, and insight. Underneath all these stages, various technologies are used, and they should be automated in production.”
The Evolution of Control-M: From Batch to Orchestration
Control-M from BMC has been a trusted solution for managing batch jobs and optimizing complex operations since the late 1980s. With an increasingly intricate technological landscape, Control-M has evolved to support SaaS-based orchestration alongside consumption [3].
A Real-Life Example: Hershey’s and the Power of Orchestration
Hershey’s, a long-standing BMC customer, is a prime example of the benefits of orchestration and automation. Running a complex supply chain for perishable goods necessitates time-sensitive operations, making Hershey’s an ideal candidate for advanced data management solutions. The company has adopted Azure to run some ETL applications in the cloud while maintaining a complex SAP environment [4].
Orchestration and Data Pipelines: More Than Just DataOps
Data pipelines require applications above and below to function effectively. Hershey’s relies on Control-M to connect these layers, enabling the company to make data-driven decisions regarding holiday campaigns or shipping locations [5].
The Future of DataOps and Orchestration: Adapting to New Tools and Customer Demands
DataOps is a crucial aspect of BMC’s strategy, but it isn’t the only component. As Faruqui explains, “Data pipelines depend on an application layer above and below them. Hershey’s may draw data from SAP, which is a constantly evolving system.” Control-M plays a vital role in bridging this gap [6].
The future of DataOps and orchestration lies in keeping up with the ever-evolving technological landscape. Customers demand flexibility to test and adopt new tools while minimizing the need for reinventing the orchestration wheel [7].
[1] Gartner. (2016). Gartner Says by 2024, Organizations That Lack a Sustainable Data and Analytics Operationalization Framework Will Experience Significant Disruptions. [https://www.gartner.com/en/newsroom/press-releases/2016-07-18-gartner-says-by-2024-organizations]
[2] DataOps, The Next Step in Your Digital Transformation Journey. (n.d.). [https://www.bmc.com/events/dataops-next-step-digital-transformation-journey]
[3] Faruqui, B. (2021, August 6). Orchestration and Operationalization: The Next Step in Organizations’ DataOps Journeys. [https://www.bmc.com/blogs/orchestration-and-operationalization-next-step-dataops-journeys]
[4] Hershey’s. (n.d.). [https://www.hersheys.com/]
[5] Faruqui, B. (2021, August 6). Orchestration and Operationalization: The Next Step in Organizations’ DataOps Journeys.
[6] Faruqui, B. (2021, August 6). Orchestration and Operationalization: The Next Step in Organizations’ DataOps Journeys.
[7] Faruqui, B. (2021, August 6). Orchestration and Operationalization: The Next Step in Organizations’ DataOps Journeys.
