What It Is Plus How And Why Your Business Should Leverage It

A scaling company needs to store data across multiple sources (e.g. databases, files, live data feeds). Even individual teams within a department – like content marketing, brand strategy, and SEO – are likely to use multiple data sources at the same time.

It’s important to make sure that you can view, visualize, and analyze all of this data at the same time. This gives you a complete picture of the health of your business, from small projects to team projections to overall business success.

Data ingestion is the process by which all of your data can be efficiently stored in one place.

Data acquisition

At a high level, data ingestion prepares your data for analysis. In this blog post, we’re going to go into the definition of data ingestion in more detail, describe what it means, review the data ingestion framework, and highlight some tools that will make the process easier for your team. Let’s dive in.

What is data ingestion?

The data acquisition prepares your data for analysis. It is the process of moving data from a variety of sources to a single location – often to a destination such as a database, computing system, or data warehouse – where it can be stored, accessed, organized, and analyzed.

This process enables companies to get a holistic view of their data in order to use and apply the resulting knowledge and insights in their strategies.

Why is data recording important?

You may be wondering why data ingestion is so important and why your marketing team – and the company as a whole – should be using it.

As mentioned earlier, data ingestion provides a single view of all of your data. Without the ability to access, review, and analyze all of your data at the same time – as opposed to having multiple data sources visualizing your data in different formats – you would not have a clear or accurate picture of what is going well and what needs improvement.

There are data ingestion tools to make this process even easier by automating the process of integrating all of your data from different sources. That way, everyone on your team can access and share this data in a format and through a tool that is universal across your organization.

Data ingestion framework

The Data Ingestion Framework describes how data ingestion takes place – this is how data from multiple sources is actually transported into a single data warehouse / database / repository. In other words, a data collection framework enables you to integrate, organize, and analyze data from multiple sources.

Unless you have a professional build your framework, you will need data acquisition software to carry out the process. The way the tool ingests your data is then based on factors such as your data architectures and models.

There are two main frameworks for data ingestion: batch data ingestion and streaming data ingestion.

Before we define batch and streaming data injection, let’s take a moment to decipher the difference between data ingestion and data integration.

Data ingestion vs. data integration

Data integration goes one step further – instead of just stopping after the data has been transported to its new location / repository, data integration also ensures that all data, no matter what type or source, is compatible with each other as well as that Repository into which it was transported. That way, you can analyze it easily and accurately.

1. Batch data acquisition

The batch data collection framework works by organizing data and transporting it to the desired location (whether repository, platform, tool, etc.) at regular intervals in groups – or batches.

This is an effective framework unless you have large amounts of data (or are dealing with big data) – in which case it’s a rather slow process. It takes time to move batches of data and you would not have real-time access to this data. However, this is known to be an inexpensive option as it requires few resources.

2. Inclusion of streaming data

A streaming data ingestion framework transports data continuously and at the moment it is created / the system identifies it. It’s a helpful framework when you have a lot of data that you need to access in real time, but it’s more expensive because of the features that batch processing doesn’t provide.

Data acquisition tools

Data collection tools integrate all of your data for you – regardless of source or format – and store it in a single location.

Depending on the software you choose, it can only perform this function or support other aspects of the data management process, such as B. Data integration, where all data is converted into a single format.

1. Apache Kobold

Apache Gobblin is a distributed data integration framework and is ideal for companies working with big data. It streamlines much of the data integration process, including data ingestion, organization, and lifecycle management. Apache Gobblin can manage both batch and streaming data frameworks.

2. Google Cloud data fusion

Google Cloud Data Fusion is a fully managed cloud data integration service. You can ingest and integrate your data from a number of sources, then transform it and merge it with additional data sources. This is possible because the tool includes many open source transforms and connectors that work with different data systems and formats.

3. Equivalent

Equalum is a real-time, enterprise-class data collection tool that integrates batch and streaming data. The tool collects, manipulates, transforms and synchronizes data for you. Equalum’s drag-and-drop user interface is simple and doesn’t require any code, so you can build your data pipelines quickly.

Start using data acquisition

Data ingestion is a critical aspect of data management – it ensures that all of your data is accurate, integrated, and organized so that you can easily analyze it at scale and get a holistic view of the health of your business.