It is widely accepted that 90% of the world’s data has been created in the last two years alone. So it’s no wonder that analyzing and storing such astonishing amounts of data is still a relatively new challenge. As Dr. Mark Kennedy, Director of the KPMG Centre for Advanced Business Analytics at Imperial College Business School said at a recent event in Hong Kong: “one of the big challenges we’re now seeing is that data sets are getting bigger, but our brains are not… This means we need to look for techniques in analytics and visualization that make big data small enough for people to take new insights on board and act on them.”
There are a number of big data tools out there that can help you “make big data small” in order to better understand and create value from your data. Let’s take a look at two of the most popular tools and common use cases for each:
Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.
Geographic distribution – Replicate data across multiple data centers
Real-time workloads – Manage complex, read-write workloads with real-time interaction
High writes and eventual consistency – Applications that require high performance, significant write activity, and multiple concurrent threads
Complex applications – Applications that deal with large volumes of multi-structured data and require real-time, highly available data interactivity
Website content – Scalable analysis of large-volume, end-user interactions for website content such as videos, retail catalogs, or online shopping
Social media – Analysis of high-velocity, large-volume social media
Cloudera is a distribution of a Hadoop framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models.
Operational Data Store – Compliments an organization’s existing architecture to alleviate current pains, while preparing themselves for future enterprise data needs.
Data Discovery & Analytics – Accelerates the data to value process by bringing more employees and their tools closer to more data as well as enabling employees to iteratively discover and interrogate known and unknown data sets faster.
Operational Analytics – Build smarter and faster analytic applications, from recommendation engines to event detection systems.
You can further customize your specific use case with your solution with Cloudera or Cassandra by adding additional big data tools like Tableau to perform sophisticated visual analysis without having to write any code, Zoomdata for more in depth, real time analytics, and/or Trifecta to dramatically improve the productivity of transforming raw data into clean, structured formats for analysis.
Big data presents complex challenges to Enterprise IT. Generating insights requires supporting modern workloads with technology agile enough to handle a data deluge. As with any new IT options on the market, the first step is understanding how to select and run the right set of technologies for your specific needs. This is why we offer a wide range of big data tools and also why we partnered with DataStax – so that we can quickly deploy a cloud strategy for your organization that will securely dissect and analyze your data while removing the complexity, allowing you to focus on your core business goals. Learn more about our Big Data solutions on our site or get hands-on by deploying free trials of the leading Big Data solutions when you fill out this quick form.