Bigdata Analytics And Insights

Big Data Analytics

Of the entire volume of data stored electronically across the world, 90 percent has been generated in the preceding two years alone and we are adding 2.5 quintillion bytes of data to this volume, every single day. The sources of this avalanche of Big Data include digital pictures and videos, social media posts, online purchase records, cell phone GPS signals and climate information gathered by sensors.

Understandably, there has been a parallel trend for Industry to seek access to this data. To manage this mind-boggling volume, scientists view it from several distinct dimensions; the most popular concept being what is known as the 4 Vs. Newer scientists tend to add Value and Volatility to the original 4, including:

Volume: When the volume of data that needs to be handled exceeds the existing capacity of the organization.

Velocity: The pace of data generation, which is accelerated by Facebook posts, sensor-drawn data or even network/call detail records generated by telecom service providers.

Variety: Big Data is not restricted to any predefined structure as was the case in RDBMS. It comes in an amazing variety of sizes and shares such as binary bytes data generated by an MRI machine or videos, audio files or simply text, encompassing internal and external source generated data.

Veracity:With the expanding volumes and the increasing complexity of data, there is an urgent need to enhance the level of trust users invest in information. Organizations are compelled to respond by ensuring the authenticity and consistency of information shared, while safeguarding that information.

The question surfaces. Exactly how big is Big Data and how different is it from formatted data?

It is also important to question, "How useful is this data to organizations? The answer is, "As important as the competitive advantage that could accrue to businesses by extracting value from Big Data. One study states that approximately 30% of data available today is pertinent and useful.

For contemporary organizations, the most important V could be Value. Asking the right questions will help to extract value from Big Data.

Challenges

For a business house that is focusing primarily on delivering business to customer rather than accessing data, the following questions will evolve as challenges.

  • Considering the formidable volume of Big Data, will mining it escalate my costs and diminish my ROI?
  • Since we do not have the capability to handle Big Data, should we use Hadoop, HBase, Cassandra or the latest Spark technology?
  • Which are the tools and technologies to be used for analytics? R, SAS, SPSS or something else?
  • How about data security?

Our Solutions

At illume, we operate on a very simple principle:

" You know your business best; whereas we understand Big Data best, in all its complexity, and know how to manipulate data to derive insights. Why not partner with us and allow us to provide Big Data analytics solutions by using a seamless, 3 step process:

Strategize

  • Analyse Business Case
  • Confirm whether Big Data Analytics need to be employed
  • Engage client in drawing up blueprint for
    Big Data Analytics adoption
  • Plan Strategy

Experience

  • Identify area for implementing small scale prototype
  • Create flexible and scalable architecture
  • Implement a proof of concept (POC) to validate starting hypothesis for success
  • Evaluate

Adopt

  • Envision iterative strategy to adopt Big Data Analytics
  • Implement actual cases based on priority and complexity
  • Measure ROI and evaluate investment
  • Increase breadth strategically and secure competitive advantage

Our Strengths

illume provides end-to-end capability to strategize, experience and adopt Big Data analytics.

Data

  • Possesses end-to-end capability to deliver strategy, experience and application of Big Data analytics.
  • Our team is empowered by substantial, cumulative and collective experience in handling Big Data and conducting big ticket implementation.
  • We have expertise in Hadoop, HIVE, HBase, Cassandra, Impala, MongoDB and Spark.
  • We implement both on-premise and cloud-based solutions. Cloud may be private or public, backed by leading vendors, including AWS and Rackspace.

Modeling

  • illume Analytics Innovation Lab' was created with the sole objective of designing analytics solutions for data-related business problem. Tie-ups with leading colleges translate into a distinct advantage, allowing us to accelerate the delivery of our solutions, banking on the services of highly qualified statistical experts.
  • We implement our solutions with client needs as our priority, using our expertise in R, SAS and SPSS

Visualization

  • We apply advanced visualization tools such as Tableau, YellowfinBI and Zoomdata, with consummate expertise
  • We deal in custom visualization, using D3.js, node.js, HTML5 etc.
  • We implement popular reporting tools, including SAP Business Object, Microstrategy and open source tools like Pentaho.
  • We partner with you in resolving your problem, using the iterative Agile development process. You can bank on our expertise!
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