CIOTechOutlook >> Magazine >> September - 2016 issue

GrayMatter: Harnessing Big Data for Proactive and Predictive Business Insights

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Burgeoning data volumes is a reality assuming gigantic proportions with every passing day. Competitive advantage in businesses is increasingly becoming contingent on deciphering such Big Data!

GrayMatter recognizes this and has dedicated practices for Big Data and Data Science respectively that focus on integration of big data from customer source systems including ERP, CRM, machine log files, social media feeds etc. and analyzing the same using advanced analytics.

Mr. Vikas Gupta, CEO, GrayMatter Software Services, articulates “GrayMatter is poised to address the growing Big Data & Data Science needs. Our pre-built solutions specific to industry verticals and horizontals, as well as custom services address critical advanced analytics problems". Some of the key pre-built solutions include GrayMatter’s Car Park Revenue Management solution that provides dynamic price optimization for car parks and thereby maximizes car park revenues. GrayMatter’s claim predictive model minimizes cost of insurance claims.

Besides pre-built solutions, the services offered include Big Data architecture consulting, capacity planning, data modelling, data integration (ETL), data indexing, data governance & quality, support & managed services, reporting, visualizations, predictive models and statistical programming. GrayMatter has a focus on SAP HANA, to handle increasing data volumes and to enable faster in-memory processing. GrayMatter possesses capability to integrate SAP and Pentaho with the open source Hadoop. GrayMatter also has expertise to extract data from No SQL databases (e.g., MongoDB, Cassandra) as well as handle super-fast computing technologies like Apache Spark. GrayMatter has proven expertise on tools like Microsoft R, SAP PA and SAS.

“It’s been an exciting journey for us from open source BI with Pentaho, to pre-built industry analytics solutions to cloud BI and now Big Data and Data Science” adds Vikas.

GrayMatter has a consultative approach to define customer problem(s) and address key issue(s) to deliver business benefits. Take a look at one of the Big Data engagements for an automotive manufacturer looking to reduce warranty claims costs, prevent brand dilution and leakage of likely repeat customers in after-sales phase. The faults and repairs data came for several parts from several service centers across the globe and hence volume of data was BIG! GrayMatter handled data on Hadoop and analysed to identify top N regions/programs, based on claims costs. Detailed analysis led to symptom identification, repair diagnostics and enabled batch and material-wise insights. In summary, the solution did root cause analysis, from field failure to manufacturing process, on data integrated from entire production process machine log as well as test results. This enabled identification of claim types accounting for majority of claim costs, correlation between demographics, geography and nature & frequency of claims, assessing suppliers based on quality, identifying and mitigating fraudulent claims etc.

The utility of Big Data processing and Advanced Analytics is only as good as the data quality. GrayMatter has defined data governance policies that provide framework for data quality assurance and enable assessment, management, usage, improvement, monitoring, maintenance and protection of data. Prompt data stewardship ensures implementation of data governance policies. GrayMatter uses automated testing tools to validate
data quality.

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