Organizations that treat data as a business asset look for ways to transform the entire business ecosystem into a data-driven entity.
Yet, aligning business goals with data goals is neither easy nor straightforward; a systematic and well-defined Data Strategy must be conceived and developed to take the data-enabled business practices forward. In this Data Strategy 101 article, we will look at the definition of Data Strategy, as well as best practices, challenges, and roadmaps.
Here's how data ingestion pipelines fit in the broader data management ecosystem.
Data engineering teams have access to a tremendous amount of information. However, collecting and consolidating all this information efficiently is hard, especially as companies add more and more data sources to the mix. This is where having well-designed data ingestion pipelines comes into play.
Data ingestion pipelines are a crucial part of the modern big data management ecosystem. They are how businesses pull information from the real world and transform it so that it can create tangible value.
As organizations grapple with ever-increasing amounts of data, the limits of the big data movement are becoming clear.
Over the last two decades, big data has provided benefits in the form of cutting-edge software that made the generation, collection, and amalgamation of data widely available to organizations. These positive impacts are both wide-reaching and apparent from optimal route planning in aviation to fraud detection and risk management in the financial sector and even tracking infectious diseases on a federal level.
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