How TechStar Ensures Your Success in Data Management & AI Services.

When looking for a company with high technical expertise in delivering Data Engineering and Data Analytics services, TechStar is the company you need. We excel at helping you store, manage, and analyze your data for your business success. Here is more on where we shine as a data management solutions company.

Data Engineering Services

To make sure your data is stored and managed properly, you need Data Engineering Services. With TechStar’s Data Engineering capability, we can help your business build the right strategy, provide architectural consulting, and ensure the right data management implementation on multiple big data platforms. We are skilled at developing and maintaining unified data with secure access to enterprise information. To make data management even more efficient, we are able to enhance a data platform with technologies that make stream processors capable of fast computation. We are also skilled at working with multiple data streams when building a streaming analytics platform.

Our Data Ingestion Framework allows us to build a unified framework for extracting, transforming, and loading large volumes of data from various data sources into the Hadoop ecosystem with Spark, Talend, and Sqoop technologies. With our Data Lake Management of Data, we can help you integrate all data into the Data Lake to generate insights across portfolios. Further, we can unify the platform for analytics with data integrity. Our expertise with Click Stream Data Feed, drawn from Adobe Analytics, allows us to:

• compile Adobe catalyst data for customer journey analytics
• generate insights from web portals to enhance user experience on your website
• understand user navigation behavior
• enhance customer experience.

With our Business Intelligence and Reporting service, your business can understand and better utilize the data it receives from its customers. Our technologies allow your business to have:

• a reporting dashboard of enterprise application data, providing insights on billed revenue, revenue traceability, funnel, and bookings metrics of the customer processed data, using IBM Cognos, OBIEE and Tableau
• reporting of fully integrated data from Salesforce and billing systems.

Case Study 1: Data Ingestion Framework

Data ingestion framework does exactly what it says it does. It takes in data from varied sources with reliability, consistency, auto schema evolution, and transformation support. It effectively combines batch and streaming data pipeline processing with modern data transformation and manipulation capabilities. This platform leverages the power of Apache Spark, Kafka, and Sqoop among other cutting-edge open-source technologies valued for their scalability.

ML/AI Platform Offerings

Once you collect your valuable data, you would like to extract as much useful information from it as possible, as fast as possible. With our Data Science services, we can create business solutions for your business, using machine learning algorithms. Those algorithms enable efficient workings of the entire data lifecycle, from raw data collection to actionable business insights.You’ll benefit from our Insight Extraction from Voice of Customer Data by utilizing our Voice of Customer application. It will perform topic modeling and sentiment analysis for low cost and increased accuracy. It will enable you to extract sentiment and key topics from product reviews, sales performance reviews, tweets, and surveys to understand what customers say and feel about your products and services.We can further help you with your Sentiment Analytics and Data Mining needs. We can use unstructured text data through machine learning and natural language processing. This type of analysis highlights significantly negative sentiment, so you can execute your quality control well and take proactive corrective measures when necessary.To act on negative customer experience swiftly, you need real-time analysis of customer feedback. We can deliver real-time analysis of incoming customer sentiment in ETMS incident management through direct NLP sentiment analysis.Matching Customer Information Across Multiple Data Sources will allow you to have a fuller picture of your customers. To aid with this task, we integrate and map subscriber names to closely matching standard scrubbed data. We are also able to create NLP-based ML solutions, using algorithms including fuzzy logic matching data.To aid with your business decision-making, we are also delivering Opinion Analytics. That means we can analyze and derive insights from customer comments’ data collected from enterprise customers.Making further use of the data, we are able to build a supervised prediction model to (a) predict customer sentiment and (b) issue category as part of the multi-class classification.The bottom line is, by analyzing customer sentiments and automated routing of ticket creation for reported issues, your business will enjoy reduced operation costs and improved customer experience.

Case Study 2: Core Sentiment Platform on Incident Management System

To drastically improve our enterprise customer’s ticket management system, we built NLP-based Sentiment Analysis framework with 95% precision. It allowed our client to execute proactive management of enterprise repair tickets. In creating this system, we employed sentiment analysis using machine learning algorithms with an optimized Ensemble Method. Various preprocessing techniques, helpful for boosting the accuracy of machine learning algorithms, were added to the framework. The resulting product also improved the customer experience of incident management by providing them with valuable updates in a simple and meaningful way. The solution was built with a combination of Rule-based classifier and ML-based classifier and Ensemble methods with Logistic regress, SVM, and Random Forest Algorithms.

Case Study 3:  AI for Intelligent Routing

To enhance the customer experience further, we implemented customer analysis and automated routing of ticket creation in response to customer-reported issues. To ensure the company stays proactive when managing their enterprise repair tickets, we developed AI-based intelligent routing of queries and responses. AI can infer real-time incoming customer sentiment through NLP sentiment analysis. Inferring customer sentiment allows for more precise routing of incident management. Better managed incidents mean happier customers and employees, and a healthier bottom line for your business. Once customer inquiries are collected through voice, digital, or social channels, rules are applied to route a particular inquiry to the agent best fit to resolve the issue. Intelligent Routing increases customer satisfaction by reducing the number of times a customer is transferred or put on hold, and it decreases the average handle time. AI also allows us to unify interaction data across channels to create customer profiles and inform business rules. To increase efficiency further, you can assign every interaction to a universal queue based on those unique rules. Handling the customer inquiries and interactions in this way improves customer service while delivering desired outcomes for the business.

Case Study 4: Location Intelligence

To help our enterprise customers with selecting optimal Hotspot hub locations, we use location analytics. Location analytics uses data from disparate sources to understand the different geographical and spatial factors to predict the best location for our enterprise customers.

With our solution, developed using a Geocoding-based clustering algorithm with geocoded addresses, we can spatially show the address locations and analyze the emerging patterns.

We are using customer-requested geolocation data to perform a clustering algorithm. As a result, we get several clusters – each with the closest to its Hotspot hub.

Summary

When looking to capitalize on the latest data management and analysis technology, you need data engineering and analytics services. TechStar, with its unparalleled expertise in data management and analytics, can help you handle and extract insights from your data in the most efficient way for your business. As a result, your business will run smoothly, and you will be well-equipped to make sound, data-driven business decisions.

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