An important question, a question that is keeping data professionals at night, is how can businesses make more data available to more users?
Currently, the demographics of enterprises have evolved. They have become sophisticated in their big data approach and they have access to a modern IT infrastructure that leverages AI.
But the biggest challenge these evolved enterprises are facing is that the demand for data has increased; more people want more data. This demand can be proactively handled with a powerful data ingestion approach. In this blog post, you’ll find what data ingestion is and how it can help companies meet ever-increasing data demands of people without difficulty.
Data ingestion strategy proves beneficial for modern enterprises, especially when their need for data intensifies, say for example when they’re acquiring another firm or starting a new project. It involves the process of data transportation from myriad sources to a destination called data warehouse or database where it can be accessed, analyzed, and used.
Acting as the backbone of data analytics, data ingestion empowers everyone in the business ecosystem who owns an application or dataset (with right tooling and right process) to ingest their data into a data lake. It can also automate cataloging of the data and allow basic governance processes for data, making data discoverable and available easily.
Data approach is the first step of a data strategy. Though it sounds arduous, fact is, it is simple and effective. Meaning, you need not know about a lot of data aspects including how the data is going to be used and what kind of advanced data manipulation and preparation techniques companies need to use. Instead, you just need the right tool and know the right process to set the path forward. However, you must take two steps to fulfil the objective.
Step 1: Make data discoverable and available: Make sure to catalog everything you ingested using automated ways. Automated techniques will not only help you handle a lot of data at once but also maintain accuracy.
Step 2: Trigger basic governance: After cataloging data, data enablement processes must be triggered that can facilitate data interactions between individuals.
Once these steps are executed successfully, companies can expand their data usage and eventually outrun their competitors easily.
Data ingestion solutions help healthcare organizations store patient health records that are used for further analysis. Let’s explore this real-world case scenario in detail.
Suppose a medical specialist is all set to perform a surgery. He or she can use information stored in the database (post data ingestion) to evaluate risks if any before and during the operation so that preventative strategies can be easily applied.
Medical units can use modern data ingestion techniques to store data extracted from the patient’s medical history etc in real-time or batch to evaluate it in detail. If the data collected indicates a huge risk, the specialist will treat the patient using a minimal-risk procedure. If the risk is low, a regular procedure will serve the purpose. Therefore, with the help of the data ingestion approach, the success rate of critical surgical processes can be increased.
The best way to start the data ingestion approach is with a pilot. The pilot must include one or two different domains and one or two ingestion patterns (like data ingestion, streaming ingestion etc.) Note, in cases where businesses need to ingest data into a cloud data lake, you’ll need cloud-based tools that fit requirements in toto.
The pilot will include people, process, and product. However, I’ve put more emphasis on process and product as our tools are efficient and simple enough to perform data ingestion. Connect with our proficient experts to know how our large file data ingestion solution can help your business increase data usage and thus corner business landscape.