Data is the lifeline of analytics, and taking the data from the source to the destination and making it analytics-ready is critical to the data lifecycle. This process is often referred to as data ingestion.

Interestingly, many enterprises out there are sitting on a goldmine of data that’s just waiting to be analyzed. Some of them have been waiting for years, others for decades.

The reason? – Data ingestion nightmares.

If your enterprise relies on Big Data Analytics to drive decisions but encounters obstacles when it comes to data ingestion, then this blog is for you.

Data Ingestion is Complex & Challenging

Here’s a quick quiz: Which of the following statements can you relate to?

I am often stuck waiting for my developers/data engineers to ingest incoming data. Their idea of "soon" feels like forever.

My current data ingestion solution gives me more headaches than wins. Inaccurate, incomplete, and untrustworthy data frequently enters my systems.

My business misses out on critical data (coming from unstructured and poly-structured sources, for example) that my data ingestion tool cannot handle. This leads to poor insights and bad decisions.

If one or more of the above statements resonate with you, you have probably hit a data ingestion roadblock. But, trust us when we say this, you are not alone.

Although Big Data Analytics starts with getting the data in, data ingestion often gets pushed to the back burner. Then, bam! Data starts pouring in at tremendous velocity from all directions across hundreds (or thousands) of diverse and disparate data sources, and data teams are left scrambling like cats in a bath, wondering how they'll ever keep up!

By the time the panic button is pressed, it’s already too late.

Enter Self-Service Data Ingestion

Self-service data ingestion uses intelligence, automation, and standardization to allow users to take control of the data ingestion process while achieving unprecedented speed, accuracy, and reliability in the data ingestion process.

At the heart of self-service data ingestion are the following capabilities–

Both technical and non-technical users can independently bring in data from various sources.
Users can easily add new data sources and specify the destination for the data.
Data pipelines, once configured, can be reused, leading to rapid and efficient ingestion of data.
Users can configure the ingestion process according to their needs, i.e., they can instruct the system to clean, pre-process, and transform the data as per their needs with just a few clicks.
All of the above is accomplished through user-friendly interfaces or tools. The entire interface is no-code/low-code in nature.
Ingestion of new data or addition of new sources does not cause schema breakage or unwanted semantic changes.

Simply put, self-service data ingestion is like having your own personal data assistant, ready to do all the heavy lifting for you. No more waiting for the tech team to save the day—instead, self-service data ingestion enables each data user to take matters into their own hands.

MECBot’s Self-Service Data Ingestion – What’s Different?

Several makeshift solutions claiming to provide self-service data ingestion are being peddled in the market. Unfortunately, while these solutions promise to take away all your data ingestion pains, they are, in effect, only slightly better than manual ingestion. It's like trying to fix a leaky faucet with bubblegum—sure, it might work for a minute, but eventually, you're in for a soggy surprise.

Introducing MECBot

MECBot by FORMCEPT is a leading data excellence platform for just-in-time decision-making. It is designed and fully orchestrated to solve key enterprise data challenges in an end-to-end manner and enables insight-driven decision-making without relying on the underlying databases or the structure of the data. This makes MECBot the go-to data analytics platform for several leading Fortune 1000 clients across the globe in industries like Banking, Insurance, Retail, Sports, Healthcare, and more.

Here is a quick video that explains what MECBot can do: MECBot Product Video

How Self-Service Data Ingestion Works in MECBot

In MECBot, the data journey begins with Domain Ontology which serves as the Global Data Definition for the entire enterprise and provides a centralized and standardized way of sourcing and organizing data with respect to the domain of the business.

Once the Domain Ontology is in place, MECBot automatically retrieves data from each source specified by the user and delivers it in a format ready for analysis. This happens automatically irrespective of the disparities in data types, semantics, sources, users, and the underlying infrastructure. With this approach, MECBot effectively eliminates the problems associated with redundant data structures.

MECBot not only auto-ingests but also automatically pre-processes all enterprise data. It then organizes, harmonizes, and contextualizes all data as per the business domain. To do this, it directly pulls the data from the configured sources and maps it to the specified Domain Ontology.

The best part? All of this happens automatically with little or no user intervention and at a fraction of the time and cost required by traditional analytics tools. Checkout the short animation below to see how it works!

Key Benefits of MECBot’s Self-Service Data Ingestion

Without MECBot, adding a new data source to a system can take days or even weeks, costing a lot of man-hours and money. But with MECBot's self-service data ingestion, this process is much quicker and cheaper. It saves a ton of IT hours and a big chunk of the data budget. Domain teams can do it themselves with just a few clicks using MECBot's easy interface, without any risks of corrupting the data in any way. Checkout the short animation below to see how it works!

In traditional data analytics tools, data ingestion happens in batches. But MECBot’s self-service data ingestion happens in real time. It’s like upgrading from a horse-drawn carriage to a turbocharged sports car! Picture this: you run an online store. If you use a traditional data ingestion tool, when a customer buys something, their purchase data might have to sit in a batch for hours before it gets into your system. But with MECBot, that data can flow in real-time, instantly updating your inventory and sales records. Plus, as the data comes in, it can automatically get organized and cleaned up. This means you can quickly see what products are selling well and adjust your marketing strategies accordingly just in time.
Data ingestion applications are typically built on top of complex frameworks like Spark, Hive, MapReduce, or Python, making maintenance and management a challenge for anyone other than IT professionals/developers. However, MECBot uses a simple, visual interface that makes it possible for anyone to securely connect to data sources, configure the data pipelines, and set up validation and transformation rules without needing extensive coding knowledge. Checkout the short animation below to see how it works!

MECBot’s self-service data ingestion solution empowers non-technical business users to efficiently manage and process large volumes of data streams while ensuring security, data quality, and an accelerated workflow. MECBot comes with built-in, customizable checks, ensuring that the ingested data is accurate and reliable. By removing this burden of creating and maintaining data pipelines, MECBot reduces IT overhead and enables the IT team to focus on more strategic initiatives.

Conclusion

To all those enterprises grappling with the complexities of data ingestion, take heart – with MECBot as your ally, you can embrace the future of enterprise data management and pave the way to success. Experience the speed and agility of real-time data ingestion, revolutionizing the way you access, analyze, and act upon your data!

Learn more about MECBot here, or request a demo to learn more about how we can address your data needs.