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What is Data Orchestration & Why It’s Essential for SaaS Business?

What is Data orchestration and why is it so much essential for your business? Read on the blog to get in touch with the details.

Simran Mohanty
Oct 19, 2021

What is Data Orchestration

What is Data Orchestration

We know that you tend to deal with an increased number of incoming and outgoing data sources. We also know that the complexity of preprocessing and post-processing on data needs time and efforts from your end. To upkeep and maintain tons of data that grows in and out of your system can be too cumbersome if not dealt with it from the beginning. So, what can mitigate these growing pain points and challenges? The answer is Data Orchestration. In this post, we will walk you through what is the definition of data orchestration and why it is essential for your SaaS business?

Table of Contents

  • What is Data Orchestration?
  • Why is Data Orchestration essential for SaaS businesses?
    1. Because it helps remove bottlenecks in Data
    2. Because it enforces the right data governance
    3. Because it helps you in maintaining data well

What is Data Orchestration?

In simple words, data orchestration is the automation of end-to-end data processes that take place across the whole of data ecosystem. To understand the entire concept of data orchestration better, we will have to break down the process into three main components which includes:

  1. Data Extraction: This is the stage where data is collected in raw form or from raw sources. First and foremost, your data orchestration tools need to apprehend and understand both your existing data and new, incoming data. Your company might have data in your legacy systems, in cloud-based tools, and in data warehouses or data lakes. In this step, the data orchestration tools help in accessing and understanding what type of data exists and its point of origin as well.
  2. Data Transformation: Data orchestration tools use data from varied formats and transform it so the data is in one standard format that is easy to understand. This makes data analysis quicker because you won’t have to spend time manually reconciling data. This is the stage wherein outliers are removed and requisite business interpretations are added. Not just that, other related metrics are computed into the system and the overall values are aggregated.
  3. Data Loading: Data is stored into storage systems such as databases, data warehouses, or data lakes. From here, data access is granted to BI tools and data scientists, who analyze data. In other words, this stage is also called as data activating phase. Activation happens when orchestration tools send the data to the tools that your company uses to operate day-to-day. That way, the data you need is already there when you need it — data loading isn’t required.

Why is Data Orchestration essential for SaaS businesses?

Because it helps remove bottlenecks in Data

As per a recently published report, it has been stated that 80% of the work linked with data analysis is mostly acquiring the data and then preparing it further. While that happens, that is where a ton of the bottlenecks come from. That is when one of the key usages of data orchestration comes into play and can drastically reduce the amount of time spent on those two steps because it’s able to automatically handle the heavy lifting of acquiring and preparing your data.

Because it enforces the right data governance

Needless to say, when your data pipeline is spread across varied data systems, data governance is difficult to keep track of and organize. As it is your data orchestration tool that links each of your data systems, it’s easier for it to enforce a data governance strategy. Remember that orchestration can organize your data in real-time and enforce that there is right data governance at all times in your system. If you’ve created a tracking plan or a data strategy framework, your tool can ensure that the data collected complies with that plan.

Because it helps you in maintaining data well

As and when your SaaS company grows, so does the need to upgrade, troubleshoot, and tune the system. While that happens, it at times becomes too cumbersome to keep track of everything happening at once. Each breaking component has downstream effects, so data engineers need to move fast to correct extraction, transformation, and loading issues. Throughout your tenure, the SaaS company sees new siloes being created, data changes that come up at the source and more. With every new input addition, maintenance becomes more and more difficult to process. That is why deploying data orchestration helps in simplifying the overall process and eases the growing pains.

Parting Thoughts

Data orchestration is preferably one of the best options for most companies with multiple data systems as it doesn’t require any massive migrations or extra storage locations for your data, which can sometimes leave you with just another data silo. But that’s not the only benefit of data orchestration. It also helps with compliance with data privacy laws, removing data bottlenecks, and enforcing data governance.

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Originally Published October 19th, 2021, Updated October 19th, 2021

Simran Mohanty

Simran hails from the content marketing backdrop with extensive knowledge in blogs, articles, and technical whitepapers in the non-fictional domain. She uses her 'gift of the gab' to explore new possibilities on her way and to make an exquisite impact on her readers. In her spare time, she likes to read journals on artificial intelligence or play with her cute kittens.

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