Information intake and ETL are typically utilized interchangeably. However, they’re not the same thing. Here’s what they indicate and how they work.
Image: garrykillian/Adobe Stock Today’s businesses have increased the quantity of data they use in daily operations, enabling them to fulfill growing customer needs and respond to problems more effectively. However, handling these growing swimming pools of service information can be challenging, particularly if you don’t have actually enhanced storage systems and tools.
SEE: Data migration testing checklist: Through pre- and post-migration (TechRepublic Premium)
ETL and information ingestion are both information management processes that can make information migration and other information optimization tasks more effective. Nevertheless, although ETL and data consumption have some overlap in function and function, they are unique processes that can bring value to an enterprise data method.
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What is information consumption?
Data intake is an umbrella term for the procedures and tools that move information from one place to another for further processing and analysis. It usually includes carrying some or all data from external sources to internal target locations.
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Batch data intake and streaming data consumption are two of the most common data consumption techniques. Batch information ingestion involves gathering and moving information at scheduled periods.
On the other hand, info collection and movement during streaming information consumption happen in or near real-time. Streaming data consumption is usually the much better of the two choices when individuals wish to utilize present data to form their decision-making procedures.
What is ETL?
ETL, or extract, change and pack, is a more particular way to deal with information. Here’s a closer look at the 3 phases:
- Extract: The extract stage includes taking information from its sources. This action needs you to deal with both structured and disorganized information.
- Transform: Transforming data includes altering it into a premium, reliable format that lines up with a company’s reporting requirements and intended usage cases. Actions taken throughout this step consist of fixing inconsistencies, adding missing worths, omitting or discarding replicate data, and completing other jobs to increase information quality.
- Load: Loading data implies moving it to its target area. Sometimes that’s a information warehouse repository that holds structured information; in other cases, information is filled into a data lake, which accommodates both structured and disorganized data.
ETL is an end-to-end procedure that allows business to prepare datasets for further usage.
How are information consumption and ETL comparable?
Despite their various goals, data consumption and ETL share many similarities. In fact, some people consider ETL a kind of information consumption, although it consists of more steps than simply collecting and moving details.
In addition, data intake and ETL can both support tighter cloud security, adding extra layers of precision and protection to datasets as they move to and change in the cloud. Both of these procedures likewise improve an organization’s overall data understanding and literacy, as they put in the time to diligently move and change their information to the right format. As a result of either information ingestion or ETL tasks, these teams will more than likely determine brand-new data security opportunities they need to take advantage of.
SEE: Top 5 finest practices for cloud security (TechRepublic)
Lastly, assistive software application is offered for both ETL and data consumption procedures. Although some services are strictly developed for one or the other, the overlap in what these procedures do suggests numerous information ingestion items carry out some or all of the steps of ETL.
How are information intake and ETL various?
Data teams normally use ETL when they want to move information into an information storage facility or lake. If they pick the information ingestion route, there are more potential locations for data; for example, information consumption makes it possible to move information straight into tools and applications in the company’s tech stack.
SEE: Task description: ETL/data warehouse designer (TechRepublic Premium)
In addition, data consumption involves collecting raw data, which might still be afflicted with various quality issues. ETL, on the other hand, always includes a stage in which info is cleaned up and changed into the right format.
ETL can be relatively slower than information consumption, which generally takes place in near-real time. A data warehouse may receive brand-new information once a day or on an even slower schedule. That reality makes it tough and in some cases impossible to access info right away.
Can information consumption and ETL be used together?
Many companies use information consumption and ETL strategies all at once. How and when they do that largely depends upon just how much information they should manage and whether they have existing infrastructure to help with the project. For example, if a business does not have an information warehouse or lake, it is probably not the best time for them to focus on establishing an ETL technique.
SEE: Cloud information warehouse guide and checklist (TechRepublic Premium)
One of the primary advantages of information intake is that it does not need a company to go through an operational transformation before it starts the process. The main thing these companies need to focus on is pulling data from trusted sources.
Nevertheless, when pursuing ETL as an information management method, companies might need to expand their current infrastructure, work with more staff member and purchase extra tools. In comparison, information ingestion is a relatively low-skill task.
Getting going with information intake and ETL
Enterprises should examine their information priorities first before they decide when and how to use data intake and/or ETL. Data experts ought to question how information intake and ETL support brief and long-lasting objectives for utilizing information in the organization.
The main point to remember is that neither data consumption nor ETL is the widely finest choice for every data job. That’s why it prevails for companies to use them in tandem.
Read next: Best ETL tools and software (TechRepublic)
