Big Data Analytics Guide > Enterprise Analytics
Enterprise analytics is a type of big data analytics that applies statistical analysis techniques to large data sets stored across an enterprise with the objective of extracting meaningful insights and making better, faster, data-driven decisions.
The techniques used to collect, analyze, and process enterprise data sets include data discovery, data mining, predictive modeling, correlations, graph analysis, and data visualization. These techniques are used by data analysts to extract meaningful data from raw data repositories that will help provide insight, highlight hidden relationships, provide context, and predict future scenarios.
Enterprise data analytics combines these analytics techniques with data management, data engineering, and strategy development to enable businesses to refine and analyze massive, historical and real-time data, and make better business predictions.
There are four main types of enterprise analytics: descriptive, diagnostic, predictive, and prescriptive analytics.
Enterprise analytics can be used by any large business that manages massive data sets and wants to improve business decisions, stimulate business growth, improve efficiency, speed up decision making, and improve financial performance. More and more companies are implementing enterprise level analytics as the volume complexity of the data they are faced with increases.
Enterprise analytics is often used by highly technical data analysts, data scientists, and statisticians, but there is a growing number of enterprise reporting and analytics solutions that make enterprise analytics more palatable and valuable for the average business user.
Important enterprise analytics trends that are shaping our relationship with data include: data quality management, voice and Natural Language, embedded and collaborative Business Intelligence, and cloud-first technologies. Learn more about specific use cases of enterprise analytics in our guide to big data analytics examples.
An enterprise analytics platform is a web analytics platform that automates the data analysis process with a variety of tools and solutions that help users define, track, and understand enterprise data. On an enterprise data analytics platform, business users can define metrics and KPIs in a centralized location, which all teams can reference to ensure all business goals are in alignment.
Enterprise analytics software can pull data from a wide variety of sources and provide a single, centralized location to store data, eliminating the risk of moving data between systems. Enterprise analytics platforms are meant to be accessible, delivering fast, actionable insights via digestible data visualizations and models that the average business user can understand. With HEAVY.AI’s Converged Analytics platform, users can take advantage of both scalability and interactivity for accelerated insight in a variety of use cases.
Enterprise analytics tools empowers business leaders to easily study and fully utilize their enterprise data, taking the guesswork out of improving business processes and performance. Enterprise analytics solutions provide a flexible, customizable platform where decision makers can track, measure, visualize, and analyze data that will provide insight into the efficiency of the enterprise.
There is no one-size-fits-all enterprise big data analytics tool, but there are a wide variety of solutions that serve different purposes for different needs. Some of the most common enterprise analytics tools include:
A HEAVY.AI dashboard for enterprise analytics
Developing an enterprise analytics strategy is a crucial step in using advanced analytics successfully. An enterprise data analytics strategy is a clear, frequently-updated guide that outlines the enterprise’s specific needs and empowers business users to take full advantage of the data available.
An effective enterprise data and analytics strategy should help accomplish the following:
With enterprises collectively facing hundreds of exabytes of data, advanced analytics solutions are absolutely essential to our ability to determine which data will actually provide meaningful, actionable insights. Enterprise analytics solutions like HEAVY.AI’s visual analytics platform automate this process and translate these enormous data sets into digestible formats. Enterprise analytics helps analyze competitor data, historical data (such as historical traffic data or historical snowfall data), and industry trends to further our understanding of the current market and how to best make a profit.
Enterprise data analytics is also necessary in order for businesses to keep up with the speed of the world. Customers expect more than real-time responses – they expect business leaders to anticipate their needs and predict the future. Advanced analytics, machine learning algorithms, and AI are helping businesses do just that. Predictive and prescriptive analytics produce targeted recommendations for how to achieve a particular outcome, identify issues before they occur, anticipate inventory needs more efficiently, and further define customer wants and needs.
Learn more about enterprise analytics use cases or see the fastest analytics platform in action with these interactive visual analytics demos.