Overview

We work with organizations to solve complex data related problems using algorithms, design methodologies and software in a measurable, sustainable, and results driven environment. We help our customers visualize, understand and use both structured and unstructured data, often hidden in data stores and assets (databases, spreadsheets, documents, emails, social media, etc.) to deliver real time business results. Talk us today to understand how we can help you:

  • Identify new opportunities and efficiencies using Big Data
  • Analyze patterns using new intelligence techniques
  • Build new knowledge by synthesising data from diverse sources
  • Structure data to maximize collective knowledge and to provide insights
  • Enable data visualization to support decision making
  • Track performance metrics
 
 

Knowledge Discovery

Also called data mining (or data discovery in recent times), the process helps users detect of patterns in data, uncover hidden insights in data in an interactive and visual way, often enabled by a range of software tools. We work with our customers with tools and methods to help them unearth hidden data which could potentially lead to supporting critical decision making, necessary for organizational transformation.

 
 

Data Aggregation

Adoption and usage of ICT the world over has made available knowledge, conversations, discrete and continuous data sets in digitized formats. This has opened numerous opportunities to collect and make sense of such data using a range of tools in an unprecedented way.

On our part, we collaborate with our customers to help them plan and go about Data Collection, which may include use of Web & mobile platforms to interface with various data sources. Part of our efforts also include:

  • Collaboratively brainstorming and defining types of data that are needed
  • Assessing data availability and potential sources
  • Developing a data collection method and interacting with relevant stakeholders and owners to enable the same
 
 

Data Engineering

As part of this practice, we go about obtaining data from any source, internal and external; using command line tools, writing shell scripts, automating data retrieval using languages like Python and Ruby, interfacing with APIs, using data-interchange formats like JSON to extract what we need. We then scrub (clustering, dimensionality reduction and more) the data before presenting it for analysis, and use various techniques for modelling and interpreting data. Our efforts enable customers get the most out of their data. Moreover, it is an exercise that often requires us to collaborate with their existing teams and experts. We also leverage emerging data science platforms to simplify part of our work. But for the most part, we use our grey matter.

 
 

Visualization

Making sense of complex data is our goal and we utilize best in class data visualization techniques, information design, and programming expertise to provide our customers the most bang for their buck. Our well thought out interfaces and applications help our clients better visualize, comprehend, analyze, manipulate, and utilize their data.

 
 
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