Any-User Analytics

Big Data Analysis

Sentiment Analytics

Make more informed decisions with real-time reporting on opinions and attitudes

This type of Big Data analysis is being used by EXALEAD customers in domains as diverse as product development and public policy, bringing unprecedented scope, accuracy and timeliness to efforts such as:

• Monitoring and managing public perception of an issue, brand, organization, etc. (called "reputation monitoring")
• Analyzing reception of a new or revamped service or product
• Anticipating and responding to potential quality, pricing or compliance issues
• Identifying nascent market growth opportunities and trends in customer demand

Exploratory Analytics

Unlike conventional analytics, referred to as Online Analytical Processing (OLAP), in which one seeks to retrieve answers to precise, pre-formulated questions from an orderly, well-known universe of data, exploratory analytics are all making discoveries and uncovering possibilities as you follow your curiosity from one intriguing fact to another within largely unknown data collections (hence the reason exploratory analytics are also called "iterative analytics"). EXALEAD CloudView is ideally suited to empowering non-specialist users to perform exploratory analytics on Big Data in both "pull" and "push" modes.

In the "pull" mode, EXALEAD's semantic mining tools are used to identify the embedded relationships, patterns and meanings in data, with visualization tools, facets (dynamic clusters and categories) and natural language queries used to explore these connections in a completely ad hoc manner.

In the second "push" method, users can sequentially ask the data for answers to specific questions, or instruct it to perform certain operations (like sorting), to see what turns up.

It's an approach that, unlike other Big Data technologies, allows ordinary users to tap into the potential of exploratory analytics: sampling it all in, seeing what shows up, and, depending on the situation, either acting on their discoveries or relaying the information to specialists for investigation or validation.

• Download our Practical Guide to Big Data
• Watch the Webinar "EXALEAD & Big Data: It's All About Usage"

Operational Reporting & Analytics

While exploratory analytics are terrific for planning, operational analytics are ideal for action. The goal of such analytics is to deliver actionable intelligence on meaningful operational metrics in real or near-real time.

This is not easy as many such metrics are embedded in massive streams of small-packet data produced by networked devices like 'smart' utility meters, RFID readers, barcode scanners, website activity monitors and GPS tracking units. It is machine data designed for use by other machines, not humans.

If such data is housed in a non-relational (NoSQL) database, performance barriers can be overcome, but this essential usability barrier remains. In addition, batch update processes associated with most such systems introduce data latency that is incompatible with operational reporting.

Data latency and usability issues are also roadblocks for conventional data warehouses. And certainly conventional relationship databases scale only with significant cost and complexity.

Now however, organizations are leveraging CloudView to overcome technical and financial hurdles to deliver operational reporting and analytics solutions that are simple to use and massively scalable at a very low hardware cost. These solutions are also natively engineered to deliver the global, cross-silo visibility that is critical to smart operational decision-making.

• Download our Practical Guide to Big Data
• Watch the Webinar "EXALEAD & Big Data: It's All About Usage"