Traversing the journey from data mining to business insights to business innovation

From simple data reporting to futuristic business recommendations

Predictive and cognitive analytics impact operations & provide customer insights to drive innovation
Business Impact vs. Engagement Maturity

Data analytics has come a long way from simple operational reporting to becoming the de-facto tool for business efficiency. With advances in data science technologies, data insights can help identify patterns and make recommendations based on historical and current data. This has enabled businesses to significantly personalize experiences to the customer on a 1:1 basis in scale, while identifying opportunities within the organization to better forecast revenue and costs and more.

Our expertise in predictive and cognitive analytics covers a wide range of advanced analytics and insight generation that can provide deep insights to our clients. We closely work with business stakeholders to understand their information (and analytical) needs for decision making and provide solutions accordingly. We have worked with clients to deliver insights from complex structured and unstructured datasets, including images, videos, audio, etc. Our team leverages machine learning (ML), artificial intelligence (AI) and neural network programming to deliver innovation solutions to our clients.

Deriving deep intelligence from the data

There’s no denying the fact that there’s power in data. But data mining in the traditional sense can only help to a certain degree. The value of the data is truly realized when intelligence is applied to provide insight into future possibilities. The ability of machines to self-learn and make decisions with minimal human touchpoints is predictive and cognitive analytics in a nutshell.

Here are a few services that we offer to our customers that bring in the much needed intelligence into data

Advanced analytics and AI/ML modeling

With data quality improvements, businesses are transitioning from basic business intelligence to advanced analytics. Advanced analytics help in synthesizing patterns from disparate systems to draw meaningful actionable insights from data. AI/ML models use self-learning and deep learning to provide feedback to traditional systems or offerings in a way that makes them smarter and cognitive. Below are a few use cases that we have built for customers using these techniques:

  • Customer churn and lifetime value analytics
  • Up-sell and cross-sell recommendations
  • Predicting online customer behavior
  • Weather impact on sales
  • Capacity utilization and product assortment 

Image and video analytics

This type of analytics uses tools such as facial recognition, video content analysis, image mining, character recognition and more for either image classification or object identification, depending on the project requirement.

​​​​​​​This can be used across domains for experiences such as know your customer (KYC) onboarding, invoice processing, employee productivity, gesture recognition, footfall analysis and so on.

Voice and text analytics

Speech recognition or speech synthesis is the capability of identifying speech and converting it to free text. It helps in diarization of speech, allowing for identifying individual voices for better data synthesis. For example, unstructured data, like calls can be converted into structured data for drawing insights.

This paves the way for many use cases such as, sentiment analysis, language translation, summarization, entity recognition, and topic modeling for insights

Geographic analytics

Geographic analytics is fast gaining popularity in business scenarios that depend on certain geographies for their sustenance and growth. Geo-analytics adds a spatial dimension to traditional pattern-based analytics.

Use cases include weather mapping, cropping patterns, demographic analysis, land usage, cartographic mapping, and marketing data mining to examine how different digital and physical touchpoints in various locations react to and interact with products. This is a vital consideration for offering more reliable services.

HGS's framework for predictive analytics that provides industry-specific insights

Framework for predictive analytics

Our framework for predictive analytics is aligned with cross-industry standard practices for data mining. This allows us to replicate projects at a faster pace and helps in making analytics pervasive across organizations. We build these solutions in an iterative manner with iterations focused on continuous improvement. Here's how: 

  • HGS provides analytics services across all levels of information needs to support business decision making
  • Our analytics team comprises statisticians, data scientists, data engineers, business intelligence SMEs, and project managers
  • The team is supported by domain experts to provide industry-specific insights
Overview of HGS's artificial intelligence-machine learning, and Cloud Tech Workshop
  • Review industry trends in Data, AI-ML, cloud, bots, IoT & other relevant areas
  • Device ideas to innovate with modern technologies and inject business growth
  • Create a transformation vision, goals & supporting business case
  • Define phase roadmap and execution plan

Our workshops can jumpstart your transformation initiatives

Our data strategy team includes individuals with cross-functional expertise in the areas of digital strategy, data architecture, marketing, domain expertise, design and more. We work closely with senior executives to help them outline scope, define multi-year roadmaps, identify best operating model, and recommend appropriate technology investments.

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Data and analytics-related services

HGS Digital provides end-to-end Data and analytics services support.

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Data Engineering and Business Intelligence

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Consumer and Business Analytics

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Marketing Analytics

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