Advertising & Marketing

Consumer-facing companies must be able to gather and manage the right data, develop intuitive features, and apply analytics that generate the insights effective to their action and business plan. We help manage diverse sources of information producing clean systems handling web traffic, sales, CRM, click logs, ad campaigns, and behavioral and social data helping companies improve targeting, reduce churn, or increase conversion rates. 

BigDataServe engineers leverage data science tools to create custom platforms and systems that monitor, learn, and inform our clients. With many new tech areas emerging into the market, we’re here to minimize the risk with innovation and generate campaign ROI. 


Banking & finance services

We approach solutions by examining how new sources of information can be used to improve revenue and how analytics can reduce total cost of operations. We use data science and machine learning tools to improve efficiency, optimize portfolios, and provide real-time snapshots. Our ability to execute on common financial services features financial forecasting models, analyzing customers, aggregating market and consumer data, and mitigating fraudulent behavior. 


The manufacturing industry is uniquely positioned to integrate the benefits of data science into all levels of their business. From the enterprise level, to the plant level, to the line level, manufacturing firms generate vast quantities of underutilized data that can be integrated and analyzed to better understand the intricacies of their manufacturing processes. Integrating the wide variety of data that are generated in the manufacturing pipeline into a single data pipeline allows automated views and greater control of lines, while providing more levers to pull with variables involved in manufacturing any product. Deep learning models can be applied at all levels of the manufacturing process in order to optimize production and generate the highest value.


Retail & CRM

Consumer facing companies must be able to gather and manage the right data, develop intuitive features, and apply analytics that generate effective insights for their business plan. Competitive advantage lies in the use of data streams from sales, operations, inventory, revenue, and media to improve customer acquisition, targeting, experience, and content delivery. From product recommendation engines, supply chain, pricing and promotion optimization, and customer analytics, BigDataServe can develop the business intelligence and big data view needed for retailers and manufacturers. 



The future of data analytics and machine learning in transportation has many applications and opportunities. Our solutions focus on pushing process automation and predictive metrics forward using open data methods to build tools and data capacity, putting in place strategies to gather and understand the collected information to augment decisions and derive insights.

We apply predictive analytics to answer your business questions and achieve operational improvements by examining a host of internal data sources (records, orders, smartphone use, customer profiles, itineraries, complaints, sensor data) and unlock the potential benefits of combining with external data sets (search, social media, reviews, weather, traffic, news events). Also, our logistic analysis can be applied to predict machine behavior, human behavior, and account for these external variables. This process optimization provides for less mechanical downtime, more efficient transportation routes, and increased customer satisfaction.



As often said, education is the most powerful weapon which can be used to change the world. Data-driven technologies further can augment the speed, ability, and percision of educators. We can enable in-depth focus on student’s performance, progress, and provide on-demand and personalized learning. By serving content with self-paced labs, customized curriculums, and focus on mastery-based learning, we can transparently assess a student’s ability to utilize information, not just cram for a test. While automation and adaptive learning tools can reduce time constraints and improve content delivery, advances in natural language processing and deep learning methods allow for automated grading, response, and summarization of unstructured text and images.



The value of data is realized only when stakeholders buy-in into the diverse set of technologies emerging at the provider, payer, and patient level. Enabling data-driven insights and practical AI opportunities for healthcare organizations to deliver groundbreaking medicine and patient care requires expert data scientists.

Healthcare organizations are in a unique position harness rich data and operate with greater insight: Electronic health records [text], medical images, sensor data [time-series], lab results, clinical data, hospital operational data, payer data, etc. Organizations will be able to uncover leading clinical practices, shrink research time, streamline administration, and offer new personalized engagement and discovery, such as digital health, at an industrial scale that will align individual’s decisions and actions in ways that improve outcomes.



As new innovation and applications for using advanced analytics emerges in all types of product lines and business functions, it is important to develop, test, and adopt the proper validated predictive and optimization models. As data sources and technologies become mature, the competitive advantage will go to insurance firms that incorporate consistent and predictable data science life-cycles in their approach. 

By leveraging big data technologies, such as Hadoop, ingesting real-time data, external data, and usage-based information, insurers can pose new questions and better understand many different types of risk, customer behaviors, and serve key clients more effectively. We can help create lasting improvements in analytics modeling that will also enable firms to underwrite many other emerging risks that are underinsured, including those related to cybersecurity, health, regional, and industry-wide business interruption stemming from climate and natural disasters.

New approach to Data Services

At BigDataServe, we leverage data science tools to create custom platforms and systems that monitor, learn, and inform users. We analyze interactions and data for evidencebased care, faster identification of shortfalls in adherence, compliance, and comprehensive data sharing between hospital and health insurance partners. We use predictive analytics not to reinvent the wheel, but take a value-based and operational automation approach to demonstrate the value of your data downstream. We help create smarter systems through smart data analytics.  

Big Data Serve Data Analytics envisions an analytics-driven enterprise to deal with the data duality. An analytics-driven enterprise overcomes challenges in the new-age-data-ecosystem through the most effective combination of people, process, and technology elements that support its data-analytics initiatives. An analytics-driven enterprise is also able to uncover the potential that data possesses in its entirety to the extent that it is able to monetize data. Big Data Serve Data Analytics envisages enterprises to monetize data through the following levers:

  • Customer Intimacy: by delivering delightful customer experiences driven by actionable insights that ensure revenue upside for the enterprise
  • Operational efficiency and risk management: higher efficiency through automation and insights-driven operations, and prevention of risk across the business value chain through predictive insights, which help reduce costs and in turn offer monetary gain for the enterprise
  • New revenue streams: by enabling enterprises to convert data into strategic assets that create new revenue models

Data Science tools & technologies we work with:

Python, Tensorflow, Keras & Pytorch

R Programming, SPSS & Minitab

Microsoft Excel, Power BI & Tableau

Apache Spark, SQL/ NoSQL, MongoDB & Hadoop

Professional Service Areas

Healthcare Analytics

  • Disease Detection
  • Population Health & Classification
  • Electronic Health & Medical Record Analysis
  • ER and Hospital Optimization

Marketing Analytics

  • Price and Promotion & Incentive Strategy
  • Campaign Effectiveness
  • Consumer Behavior & Segmentation
  • Customer Churn and Lifetime Value

NLP (Natural Language Processing)

  • Document Extraction, OCR
  • Text Summarization, Topic Modeling
  • Chatbots, Recommendation Engines

Computer Vision

  • Image Analysis
  • Object Detection & Segmentation & Tracking  Medical Images, Manufacturing, etc.
  • Noise Removal and Calibration

Time-Series Analysis

  • Signal Analysis and Internet of things (IoT)
  • Financial Prediction
  • Sales Forecasting
  • Consumer and Device Behavior

Business Intelligence

  • Find and Increase Efficiencies
  • Personalize the Customer Experience
  • Make Data-Driven Decisions
  • Outmaneuver Your Competition

Statistical Analysis

  • Descriptive statistics
  • Inferential statistics
  • Bayesian inference
  • Quality Control  Predictive Analytics

Data Visualization

  • Preprocess Data
  • Create Data Model with DAX
  • Visualize Data with appropriate KPIs

Data Engineering

  • Find the right approach to collecting and connecting with data.
  • Connect the dots across data silos for generating actionable insights.
  • Develop and implement big data solutions across all business verticals.
  • Identify and resolve big data security risks ahead of time.
  • Maintain and manage big data services with ease.

Anomaly Detection

  • Fraud & Fault Detection
  • Event & Risk Analysis

Let’s Introduce and Make Some Awesome Project


+1(321) 430 8283