With advancements in technology and the world moving toward digitization, every company is becoming software. With the world generating more data than ever before, modern big data technologies allow organizations to efficiently store, process, and analyze vast amounts of data. From customer behavior and shopping trends, to live traffic data and risk management, big data fuels better business decisions, improves efficiency, and unleashes correlations and predictive analytics. Learn what big data is, how it works, major benefits, and how to get started.
Big data is essentially a collection of extremely large data sets that cannot be processed by traditional tools, but that can bring a lot of value to business or society. There are three criteria for big data (3 V’s): huge volume, high velocity (constant and fast data generation followed by rapid processing), and great variety (data can come from different sources in a structured or/and unstructured form).
Data can be collected, curated, and analyzed in batch processing mode, or as real-time data streams to derive useful insights for a range of stakeholders.
As data grows exponentially in volume, complexity, at faster throughput, big data becomes crucial for any business to gain insights, improve business operations, mitigate risks, and make impactful business decisions.
By analyzing massive amounts of data, organizations can create new products, estimate the efficiency, understand how to conduct marketing campaigns, optimize their resources, formulate strategy, etc. Data can describe almost everything in business. This means that big data can generate benefits for every aspect of business activity.
There are two reasons behind the growing popularity of big data: data availability, and accessibility to computing resources.
From improved customer experiences to predictive analytics, big data brings numerous real-life benefits and use cases:
The process of working with big data involves data collection, data storing, data analysis, and decision-making. Working with big data also requires the creation of appropriate data pipelines to transfer data between the components of the big data ecosystem. Big data usually consists of the following components:
Due to the sheer volume and complexity of data, businesses often run into roadblocks. Here are the most common challenges that organizations face today when it comes to using big data:
A major challenge in modern data management is the ability to streamline all data types, from all sources and formats into a single pane. The ability to process and integrate real-time streams of data allow for digitalization, speedy time-to-market, quick innovation, and big data analytics at scale.
Confluent is a data streaming platform designed to integrate data from countless sources at scale, including traditional databases and modern, distributed architectures. Originally envisioned as a fast and scalable distributed messaging queue, it has rapidly expanded into a full-scale streaming platform, capable of not just collecting batches of data, but storage and real-time data aggregation, processing, and analytics.
See how you can start by downloading Confluent, the leading distribution of Apache Kafka and the most powerful enterprise event streaming platform in the industry, or learn more about real-time data streaming.