How CIOs Can Turn the 3 Vs of Big Data Into Business Intelligence
Big Data refers to the large volume of data that floods business organizations on a day-to-day basis. This data, which can be either structured or unstructured, has the potential to be mined for valuable business insights. But the volume of data isn’t as important as what organizations do with it. It’s the analysis that helps businesses choose the right strategies, adopt more efficient processes and make more informed decisions.
The three concepts that define big data are:
Volume: From business transactions and social media, to sensors and machine-to-machine data, the explosion of data has created demand for new technologies for analysis and advanced storage.
Velocity: Today’s information travels at an unprecedented speed and demands timely processing. Data movement, these days, has been reduced to a fraction of seconds. Technologies such as sensors, barcode readers, and smart metering are utilized to deal with torrents of real-time data.
Variety: Data, structured or unstructured, is available in various formats. From numeric data to emails, text documents, audio, videos, and financial transactions – businesses have to figure out how to manage and draw connections among huge amount of information that are in many different, sometimes incompatible, formats.
IT Operations Analytics (ITOA), also known as Big Data Analytics and Advanced Analytics, can help companies bring order to the growing data complexity.
Most departments manage abundance and everyday growing machine data, including anything from sensors and connected machines to GPS devices and meters, however many organizations can’t leverage any of it in its raw format. Companies that disregard raw data altogether risk ignoring valuable information that could impact strategic business decisions. ITOA systems can monitor and analyze that data for companies in real time to help them derive insights from the large volumes of multi-structured data.
When Too Much Data Is a Problem
Now that business have started moving to the cloud and processes have extended to the mobile web, what is the next step is to keep an eye on the moving pieces.
As application architecture advances and database technology evolves, data supervisors and their operations counterparts have had a hard time managing data volumes. This calls for a data-driven IT management practice. A centralized database performance monitoring platform monitors, manages, and optimizes database performance for every database type, wherever it resides. It offers a single-view operations tool that can maximizes the performance and the availability of database-driven applications and services.
How Companies Can Turn Data Into Intelligence
The objective of most big data initiatives is to transform how an organization accesses its data and utilizes it to capture better business insights. o enhance flexibility, open source technologies can be implemented. With centralized analytics, a single platform pulls in data from throughout the company and processes it into something meaningful. Companies can identify any areas of interest or conflict through a full-stack view of the operations.
The new breed of ITOA solutions do more than just interpreting data for companies to make decisions about the future, they can help businesses avoid potential catastrophes by sending targeted real-time warnings when any specific key performance indicator (KPI) deviates from the norm. They can capture,analyze and generate patterns to immediately identify irregularities for variables such as:
- Naturally occurring load or application usage patterns.
- IT infrastructure KPIs such as central processing unit (CPU) utilization, database storage levels, active connections.
- End-user application experience, such as responsiveness, slowness, availability.
Data is all around us and more accessible than ever. However, the enormous volume and complexity of the data has rendered many organizations unable to leverage its benefits. Operations analysis is a new generation of solutions that can interpret data volumes into useful business insights and deliver those insights to companies in real-time to help them achieve success.