What is Project Quality Management?
What actually is project quality management? Discover more about what it entails in this comprehensive and informative article.
Businesses today generate unspeakably vast amounts of data sourced from a variety of sources like websites, physical sensors, call centers, mobile apps, sales data, social channels, geolocation tools and more. That data contains worlds of useful information, full of potential value for both immediate decision making and long-term strategic planning. In order to extract its full value, that data must be directed into a data pipeline, a collection of technologies that work in conjunction to aggregate data from multiple sources for scrubbing, storage, translation, presentation and consumption by business decisionmakers.
But a data pipeline can’t be managed manually as the data comes in too quickly, the volume is too high, and the process is too dynamic. Given the speed and demands of business, today’s data pipeline must rely on automating technologies to orchestrate connections between the various data sources to make data meaningful and available anytime to the stakeholders who need it.
This makes pipeline automation essential for any business that aspires to be data-driven. Data pipeline automation allows the business to extract data at its source, transform it, integrate it with other sources and continually fuel business applications and data analytics tools.
DataOps: Aligning enterprise resources to treat data as a strategic asset
Not to be confused with DevOps, DataOps enables and unlocks value enterprise data from the moment it's created until it reaches end users in the form of usable insight. According to CIO Magazine, DataOps is “an agile, process-oriented methodology for developing and delivering analytics.” High-functioning DataOps teams use agile methodologies to collaborate across functions, transcend skill silos, and bring together members with both development and analytics expertise. By building, automating and optimizing infrastructure such as data pipelines, DataOps teams self-organize to identify and solve complex problems and serve up strategic data to users in a way that is sustainable, scalable and responsive to rapidly changing business needs.
Depending upon the nature of the business, it may use various pipeline structures, such as those listed below:
Regardless of the type of pipeline, automation is key to helping you get the most out of the data it contains. Central to your automation strategy, ideally, is some sort of orchestration platform that enables the systems within the pipeline to communicate with one another via an API or some other proprietary connector. This provides a single point of control and can make your automation efforts much more effective.
Business users, whose reporting needs are greater than ever, demand speed, scale and repeatability from data they use for both historical and predictive analysis. Data pipeline automation reduces manual tasks. It enables IT Teams — which often lack skilled data workers — to extend their limited resources and quickly help the business ingest, combine, normalize, analyze and present data continually with much less effort. This automation creates a big impact on the business with only limited resources.
While there is some effort and investment involved in putting an automation strategy in place, the benefits can be enormous. Below is a list of ways an automated data pipeline can help your business:
Data pipeline automation is no longer an exclusive capability reserved only for a handful of companies with teams of brilliant data scientists. The rapid proliferation of enabling technologies, such as pipeline orchestration platforms and intuitive BI tools, make it an exciting time to adopt pipeline automation and to hone your team’s skills in these technologies.
Armed with the right strategy, technologies and training, any business can unlock the value of its most valuable asset: the data it creates day in and day out.
There are countless tools and learning opportunities IT and business professionals can take advantage of the benefits of data pipeline automation. ExitCertified is partnered with all of the major cloud providers, so if you’re looking for AWS Data Analytics, Microsoft Azure Data and AI, or Google Cloud Data Analysis training, we have you covered. ExitCertified also has Business Intelligence training from various tool providers as well as data automation training from vendors like Databricks, Snowflake, IBM and SAP.
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