With so many business decisions requiring the use of big data, it has become more important than ever for companies to have useful data on hand. To actually derive insights from data, however, organizations need to have access to it from a single place. This is far easier said than done, especially when it comes to the ever evolving nature of the internet. To gain a competitive advantage and improve your company’s data strategies, you need to look into web data ingestion, understand its challenges, and discover the best ways to leverage it.
What is Data Ingestion?
A typical data ingestion meaning includes the overall process of collecting, transferring, and loading data from one or multiple sources so that it may be analyzed immediately or stored in a database for later use.
Data ingestion can be broken up into types as well. For example, when you ingest data, you can do it in batches. In this case, data is imported periodically, usually at regularly scheduled times. If you have processes that run at specific times, batch processing can be particularly useful. Data ingestion can also happen in real time, a good strategy when you need insights and information regularly or the data is of a time sensitive nature. You can also combine the batch and real time processing, which attempts to mix the benefits of both approaches.
Web data ingestion places information from the entire internet at your fingertips. It allows you to analyze vast amounts of data, giving you insights you never would have had before. To truly utilize web data ingestion, however, you’ll need to overcome some of the more common challenges it faces.
The Main Challenges of Web Data Ingestion
As with most things involving scale, the web data ingestion process comes across quite a few challenges. Let’s take a brief look at some of them.
Complexity tends to become a big issue for data ingestion. There are not only lots of different data sources to collect from, the number seems to be growing every day. Properly ingesting data means removing mistakes and eliminating mismatched schema, and with so many sources, that can be difficult.
The speed of data ingestion can also become an issue. The amount of web data is massive, and as volumes increase, it can be challenging to get all the data you need in the time you need it. Complicating the problem is how different data sources will often give their data at different frequencies.
Attempts to solve the data ingestion speed problem usually involve the Change Data Capture (CDC) process, which only loads changes that occur to the main data set. However, CDC on its own is a complex strategy, and many databases have difficulty updating or merging new data changes.
Another challenge involves making sure moving data is done securely. As data is staged during the ingestion process, it needs to meet all compliance standards. Failure to do so could lead to data that isn’t properly protected.
Data Ingestion Tools
To handle these challenges, many organizations turn to data ingestion tools which can be used to combine and interpret big data. A number of tools have grown in popularity over the years. Those tools include Apache Kafka, Wavefront, DataTorrent, Amazon Kinesis, Gobblin, and Syncsort. These data ingestion tools give organizations a framework to operate with as they ingest data from different data sources. They also allow people who may not be closely familiar with data ingestion processes the ability to manage it more easily through user-friendly interfaces.
Enabling Web Data Ingestion Through Web Data Integration
Data ingestion can provide your company with tremendously valuable insights, and you can gain those benefits with Import.io’s Web Data Integration platform. Data ingestion is just one part of the Web Data Integration process. During the integrate phase, web data is loaded into the customer’s pipeline, providing high-quality web data to a company’s applications, analysis tools, business processes, and visualization software.
Web Data Integration takes the bigger picture approach, and the platform offered by Import.io makes it so you don’t have to construct your own infrastructure. It also solves many of the challenges seen during data ingestion. The platform secures information and simplifies the data ingestion process while speeding it up.