How to Leverage Big Data Ingestion Solutions to Make Better Decisions

In the times when almost every company wants to drive their digital transformation initiatives, the growth of data has reached its height. The explosion of data is not only in terms of size and volume but also veracity and variety. Many reasons fuels this data outbreak, including

• Technology proliferation

• Growing infrastructure capacity

• Development innovations

With more than 2.5 quintillions of data created each day, it becomes difficult to handle these complex data streams. 

To do it effectively, companies need a modern big data ingestion tool that can help them process and use different forms of data with speed and ease. 

Modern big data ingestion solutions play a central role in transporting all this data from myriad sources into a consolidated database or data lake. Also known as data lake ingestion tools, these solutions use self-service and automation to enable non-technical business users to ingest data while freeing IT to focus on more high-value tasks. 

But before unlocking the value of the big data ingestion tools, let’s find out different data types and the associated challenges in detail. 

An Introduction to Data Types and Complexities 

The growing information is generated from a variety of data sources, whether it’s operations data, marketing data, or customer data. Customer data is information produced from different sources, such as banking records, employee benefits, business transactions, insurance claims, etc. Operations data encompasses various other data types, including online transactions, sales data, pricing data, etc. Marketing data includes web traffic data, website log data, and more. All this data in a consolidated form is called big data. 

During the processing of these highly complex data streams, technical people and analysts can extract actionable information to drive decision-making. When big data is used in a proper way, it becomes easier for companies to identify the customers’ needs and requirements, improving branding, reducing customer churn, and improving the ease of doing business. 

However, with four main components, i.e. velocity, veracity, volume, and variety, it’s difficult for companies to harness the true potential of big data and deliver value. These four attributes disturb the time and speed of data interpretation and usage. To gain a better understanding, let’s find out more information about these four attributes. 

Volume: The big data’s volume is enormous, and is normally measured in GB, TB, and Exabytes. 

Velocity: The velocity of big data slows down the processing speed, causing downtimes and breakdowns.

Veracity: The data’s veracity is the measuring value of its accuracy. Operations can get corrupted if anomalies or discrepancies are present. 

Variety: Data can be diverse. It can be semi-structured, structured, or heterogeneous. 

Owing to these four attributes, the process of big data ingestion and processing turns out to be difficult. Application failures and data flow breakdowns become evident, causing delays or information losses. Along with sabotaged accuracy, big data processing takes time and effort. 

How Can Big Data Ingestion Tools Help? 

To extract value from big data streams, companies need to ingest data properly. Modern big data ingestion solutions enable companies to ingest data from multiple sources into a data lake or warehouse. 

Modern data ingestion solutions have in-built self-service and automation capabilities that empower non-technical business users to ingest data while freeing IT to drive more high-value tasks. Because IT no longer needs to implement customer codes and build data mappings, the delays incurred reduce. This decreases overhead costs and helps companies deliver the value promised to customers much more quickly and efficiently. When customers receive the value sooner, they become happy and satisfied. This encourages them to either buy more products or services or stay longer.  

The ingested data can further be integrated and used using self-service data integration tools. The insights garnered can be used to make informed decisions and accelerate revenue growth. 

In short, self-service data ingestion solutions enable non-technical business users to process data while freeing IT to focus on more strategic business priorities, thus delivering the value promised to customers and growing revenue.