Big data analytics: translating information into knowledge

The concept of Big Data has been around for a number of years now and although businesses have started to understand the importance of streamlining and analysing all the data captured and combining this with sources of data from external sources, some are still unsure about what it is and how it can be used.

Today we are overloaded with information and this, largely driven by the internet and smartphone penetration, has ushered us into the era of big data; where large or complex data sets can no longer be processed by traditional data-processing tools.

Big data analytics works on the notion that by collecting, organising and analysing large sets of data, patterns and other useful information which were otherwise hidden, start to emerge. You have the opportunity to harness valuable insights from the data collected and derive business intelligence to improve processes, customer satisfaction and boost innovation. This value can only be unlocked by powerful analytics tools designed to handle and store the massive amounts of video, audio, text and even numerical data available to your business.

Just to get a perspective, big data represents a move from gigabytes to zettabytes (1trillion gigabytes). It includes both structured (spreadsheets, relational databases) and unstructured (email, multimedia content) data, and can be batch-processed as well as real-time/streaming data.

A big data scenario may employ one or more of these typical tools:

  • NoSQL (Ex: Hbase, Cassandra, DatabaseMongoDB)
  • MapReduce (Ex: Hadoop, MapR, Pig, Hive)
  • Storage (Ex: Hadoop Distributed File System)
  • Processing (Ex: Tableau)

Take Tableau. This platform helps both small and medium-sized as well as large businesses make sense of their data, to spot trends, drops in productivity, and identify reasons behind this loss. Rich visual, interactive data makes it easy to understand and absorb discoveries, patterns and insights. The platform easily integrates with your existing software infrastructure and offers immediate integration with some of the cloud-based apps that you may be using such as Google Analytics and Salesforce.

Tableau comes with features that address users’ requirements, allowing them to do more with the available data, all via a simple, intuitive interface. For instance:

  • A dashboard that offers a visual, interactive way to view key data points.
  • The ability to create data sets by pulling data from several sources.
  • Heat maps and tree maps.
  • Social integration and easy collaboration between users to facilitate conversation.

While big data analytics is a significant investment, the payoff can be huge if you have built a number of specific use cases around it. In general, analytics solutions offer the following indisputable advantages:

  • A cost-effective way of storing large amounts of data.
  • Analytics on real-time data improves decision-making rate and quality.
  • Identify new data sources for more comprehensive analysis.
  • A powerful way of understanding customers’ needs and challenges to create new products/solutions, and unearth new avenues of monetization.

Big data is already getting bigger with the adoption of Internet-of-Things (IoT) software. The evolution of big data analytics platforms will be a natural progression to capture value from IoT data and amplify business performance further.

If you are struggling with making sense out of your data and you would like to learn more about the benefits of Tableau Software, simply contact us today!

iMovo can get you started with a FREE demo and answer any questions you might have.

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