- Big data refers to the volume, velocity and variety of data, often called the three Vs.
- Big data is data so large, fast or complex that traditional methods struggle or fail to process it.
- Big data comes in three types: structured, unstructured and semi-structured.
- Big data lets companies make data-driven decisions instead of relying on gut feel.
- Data mining extracts patterns from data of any size; big data describes the data itself.
What is Big Data?
Big data refers to the volume, velocity, and variety of data that artificial intelligence technologies are using to discover patterns and correlations hidden in massive collections of data. Big data is also commonly known as the three Vs.
Big data consists of complex data sets often from new sources. Nearly 2.5 quintillion bytes of data are created each day and when used effectively it can be an effective asset for organizational decision-making.
Examples of Big Data
Big data is often used in products or services you use every day. Here are two examples of how big data is used to improve products and services.
Product Development
Companies like Netflix or Procter & Gamble leverage big data to anticipate market demand. Predictive models are built for new products and services by classifying key attributes of past products then modeling the commercial success of those offerings.
Customer Experience
Big data enables companies to gather data from website visits, social media interactions, and ads you click on. The data is then used to make improvements to the customer experience in ways such as delivering personalized offerings in hopes to reduce customer churn.
Why is Big Data Important?
Big data allows companies to implement data-driven decision-making rather than having to rely on feelings or subject experiences. When used effectively, big data gives companies competitive advantages in the marketplace.
Big Data vs Other Technologies & Methodologies
Big data vs data mining
Big data is a term that refers to a large amount of data whereas data mining refers to a deep dive into the data to extract the key knowledge/pattern/information from a small or large amount of data.
Big data vs data science vs data analytics
Big data refers to a large and complex collection of data. Data analytics is the process of extracting meaningful information from data. Data science is a multidisciplinary field that aims to produce broader insights.
Big data vs data warehouse
Big Data is a term applied to datasets whose size is beyond the ability of commonly used tools to capture, manage, and process the data within an acceptable elapsed time. Data-warehouse is a collection of data marts representing historical data from different operations in the company.
Big Data in H2O AI
H2O-3, the open-source distributed machine learning platform, builds models on big data in memory and scales across a cluster. H2O-3 docs.