Data Analytics

Develop strategic plans for your business with our invaluable data analytics services. We build robust infrastructures for data aggregation, analysis, and reporting to supercharge your decision-making and propel your business to new heights of success.

Trusted by startups
and Fortune 500 companies

Data Analytics Services We Offer

Experience the power of our specialized big data analytics as a service, empowering data-driven decision-making. Unleash the full potential of your data with our customized data analytics and business intelligence services, designed to deliver actionable insights and drive strategic growth for your business.


BI Consulting

Leverage our business intelligence consulting services gain actionable insights. We design and develop efficient data warehousing solutions, create interactive dashboards and reports for visually impactful insights, implement data quality management techniques, and optimize query performance to maximize system efficiency.

BI Implementation

Streamline your data analytics journey with our comprehensive BI implementation services. We handle data source integration, ETL processes, data modeling, and report/dashboard creation. We provide user training and ongoing support, ensuring a seamless implementation process for data-driven decision-making.

Big Data

Harness the power of big data with our advanced big data analytics services. We handle data ingestion and integration from diverse sources, perform data cleansing and preprocessing, apply machine learning and AI algorithms for advanced analytics, enable real-time data processing, and ensure scalable storage and infrastructure management. Unlock valuable insights for strategic growth.

Managed Data Analysis

At TechIND, we go above and beyond to provide comprehensive managed data analysis services. Our team collects and processes your data meticulously, ensuring accurate and reliable insights delivered to you promptly. Whether you require one-time analytics or recurrent analysis, we are committed to meeting your specific needs and empowering you with actionable information.

Data Analytics Modernization

Our expertise in data analytics modernization enables us to revamp your existing analytics solution, enhancing its capabilities to unlock maximum return on investment (ROI). We work closely with you to understand your evolving analytics needs and apply cutting-edge technologies and methodologies to transform your data infrastructure.

Data Management Services

Efficient and effective data management is the cornerstone of successful analytics initiatives. Our data management services encompass the entire data lifecycle, from collection to storage, access, security, and analysis. With a robust data management framework in place, we streamline your operations, ensuring data integrity, compliance, and accessibility.

Data Integration and Data Warehousing

Integrating disparate data sources and centralizing them in a unified repository is key to gaining holistic insights. Our expert team specializes in designing and implementing Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) processes. We seamlessly integrate your data, transforming it into a structured and consistent format for analysis.

Data Science

Harnessing the power of data science is paramount in today’s data-driven landscape.We handle the complex task of cleaning, organizing, and optimizing your data, ensuring its suitability for advanced analytics. Moreover, we specialize in developing and fine-tuning machine learning models, including cutting-edge techniques like deep learning.

Business Intelligence

Effective business intelligence requires a well-designed infrastructure that facilitates seamless analytics querying and reporting. Our experts work closely with you to understand your business objectives and design a tailored solution that aligns with your needs. We enable ad hoc and scheduled analytics querying and reporting, empowering you to gain real-time insights into your data.

Artificial Intelligence

Leveraging artificial intelligence (AI) can revolutionize your data analytics capabilities. Our comprehensive AI services cover various aspects of the analytics workflow. We handle data gathering and cleansing, ensuring high-quality input for training your machine learning (ML) models. Our team excels in ML modeling, applying state-of-the-art algorithms to unlock valuable insights from your data.

Data Visualization

Visualizing data is crucial for effectively communicating insights and facilitating understanding. Our data visualization services go beyond simple charts and graphs. We offer interactive dashboarding solutions that allow for dynamic exploration of your data. Whether you require custom visuals tailored to your unique requirements or prefer pre-built visualizations, our team has the expertise to bring your data to life.

Let’s Discuss Your Project

Get free consultation and let us know your project idea to turn it into an amazing digital product.

Our Technical Expertise in Data Analytics

Our technical proficiency in data analytics empowers us to extract actionable insights, uncover valuable patterns, and drive data-informed strategies that propel business growth and success.

Programming Languages

  • Python
  • R
  • SQL
  • Java

Data Processing Frameworks

  • Apache Hadoop
  • Apache Hadoop

Data Visualization Tools

  • Tableau
  • Power BI
  • QlikView

Machine Learning Libraries

  • TensorFlow
  • scikit-learn
  • PyTorch

Data Integration Tools

  • Apache NiFi
  • Informatica PowerCenter
  • Talend

Natural Language Processing Libraries

  • NLTK
  • SpaCy
  • Gensim

Use Cases of Data Analytics

Data analytics finds practical applications across industries, enabling organizations to make data-driven decisions, uncover hidden patterns, and gain valuable insights for improved operational efficiency and strategic decision-making.


Financial Analytics

Data analytics can be used for monitoring company revenue, expenses, and profitability, profitability analysis and financial performance management, budget planning, and financial risk forecasting and management.

Customer Analytics

Leverage the power of data for customer behavior analysis and predictive modeling, customer segmentation for personalized sales and marketing campaigns, cross-selling and upselling offers etc.

Sales and Product Analytics

Businesses are using data for analyzing sales channels, pricing strategies, sales trend identification and prediction, product performance analysis, tracking customer interaction etc.

Sales and Product Analytics

Businesses are using data for analyzing sales channels, pricing strategies, sales trend identification and prediction, product performance analysis, tracking customer interaction etc.

Asset Analytics

With data analytics, you can do real-time asset monitoring and tracking, predictive and preventive maintenance, asset investment planning, and asset usage analytics.

HR Analytics

Monitoring and analyzing employee and department performance, employee satisfaction analysis, retention strategy optimization, employee hiring strategy analysis, and labor cost analytics.

Transportation and Logistics

Capacity planning and optimization, predictive maintenance for vehicles, vehicle demand forecasting, fuel consumption optimization, and IoT data analytics for safe cargo delivery.

Manufacturing Analytics

Data analytics can help with overall equipment effectiveness analysis and optimization, manufacturing process quality optimization, equipment maintenance scheduling, power consumption forecasting etc.

Healthcare Analytics

Healthcare facilities are using analytics for patient health monitoring and alerting, treatment optimization, patient risk assessment, proactive care etc..

We Are India’s Top

Company Empowering Businesses with Data Analytics Services

As a leading data analytics services company, we deliver exceptional solutions and experiences. We tailor our data analytics consulting services to meet your unique business requirements, drive efficiency, and ensure your business. Partner with us to unlock new possibilities.

  • Cost-effective Solutions
  • IP-rights protection
  • Flexible engagement options
  • Smooth communication
  • CMMI level 3 company
  • Experienced data analytics consultants

Awards & Certifications –


We are Trusted by the Top Industry Leaders

We enable businesses worldwide to thrive, evolve, and seize a competitive edge in the data-centric era. With our customer-centric ethos, we serve a wide spectrum of clients, encompassing startups, enterprises, product firms, digital agencies, SMEs, and government entities. Our bespoke solutions for data analytics and BI development are meticulously crafted to align with your distinct technological needs.

  • Quick team scaling
  • Time-zone compatibility
  • Global quality standards
  • Client-centric approach
  • Ongoing learning & development programs
  • Cutting edge infrastructure

Got a Project in Mind? Tell Us More

Drop us a line and we’ll get back to you immediately to schedule a call and discuss your needs personally.

User Guide to Understanding Data Analytics

Is Data Analytics the same as BI?

While data analytics and business intelligence (BI) are related concepts, they are not the same. Let’s understand the difference between the two:

Data Analytics: Data analytics involves examining, transforming, and analyzing data to uncover insights, patterns, and trends. It involves applying statistical and analytical techniques to raw data to gain meaningful insights and make informed decisions.

Data analytics focuses on extracting valuable information from data sets, often using tools and technologies like statistical modeling, data mining, machine learning, and data visualization.

Business Intelligence (BI): Business intelligence refers to the technologies, strategies, and practices organizations collect, integrate, analyze, and present business information.

It involves gathering and organizing data from sources, transforming it into meaningful information, and delivering it to decision-makers through reports, dashboards, and visualizations.

Overall, data analytics focuses on data analysis to extract insights, while business intelligence involves collecting, integrating, analyzing, and presenting data to support decision-making and provide a comprehensive view of the business.

Data analytics is a subset of business intelligence, as it contributes to the analytical component of BI.

How can data analytics and business intelligence help a business grow?

Data analytics and business intelligence have become indispensable tools for businesses seeking sustainable growth in today’s data-driven world. Here are some key ways in which data analytics and business intelligence contribute to business growth:

Make informed decisions: By analyzing vast amounts of data, businesses can identify patterns, trends, and correlations. It can help them make crucial decisions across various departments, such as marketing, sales, operations, and finance increasing the likelihood of making sound, data-driven choices that drive growth.

Identify market opportunities: By analyzing market trends, consumer behavior, and competitor performance, businesses can identify emerging opportunities and potential gaps in the market.

This insight enables companies to develop innovative products or services, tailor marketing strategies, and enter new markets, fostering growth and expanding their customer base.

Optimize operations: By analyzing operational data, businesses can identify bottlenecks, inefficiencies, and areas for improvement.

Businesses can reduce costs, improve productivity, and deliver products or services more efficiently by making data-driven optimizations.

Understand customer behavior: Data analytics and business intelligence provide businesses with valuable insights into customer preferences, purchasing patterns, and satisfaction levels.

Gain competitive advantage: Data analytics and business intelligence enable businesses to gain a competitive edge in their industry.

Businesses can identify unique selling points and differentiate from competitors by analyzing competitor data, market trends, and consumer insights, helping to develop targeted marketing strategies, refine offerings, and respond to market changes.

How does business intelligence and data analytics work together?

Business intelligence (BI) and data analytics work together to provide organizations with valuable insights and support data-driven decision-making. Here’s how they complement each other.

Data Collection and Integration: Business intelligence systems gather and integrate data from various sources, such as databases, spreadsheets, and external systems. Data analytics relies on this consolidated data to perform in-depth analysis and extract meaningful insights.

Data Cleaning and Preparation: BI systems often include data Clean and well-prepared data is crucial for accurate data analytics.

Data Exploration and Visualization: Business intelligence tools provide dashboards, reports, and visualization to help users understand trends, patterns, and relationships within the data. Data analytics leverages these visualizations to identify areas for further analysis and effectively communicate findings.

Descriptive Analytics: Business intelligence systems typically provide descriptive analytics, which involves summarizing historical data and presenting key performance indicators (KPIs).

Data analytics can further explore descriptive data by applying statistical techniques, data mining, or machine learning algorithms to uncover insights, correlations, and causations within the data.

Diagnostic and Predictive Analytics: Data analytics goes beyond descriptive analytics by utilizing diagnostic and predictive analytics. It involves analyzing historical data to identify factors that contributed to results.

Predictive analytics, on the other hand, uses historical data to build models and predict future outcomes. These advanced analytics techniques enable organizations to make proactive decisions.

Decision Support: Business intelligence systems provide decision support capabilities by presenting aggregated data, trends, and performance metrics. Data analytics enhances this decision support by providing more granular insights, predictions, and recommendations based on sophisticated analysis techniques.

Organizations can make more informed and precise decisions by combining BI with data analytics.

Combining BI with data analytics: BI systems and data analytics work cyclically. Organizations use business intelligence to monitor and measure their performance, and data analytics helps identify areas for improvement.

Insights gained through data analytics can then be fed back into the BI system to refine KPIs, reports, and data collection processes, ensuring continuous improvement in decision-making and business operations.

What is the relationship between data analysis and data analytics?

A few key characteristics of backend technologies separate the good from the great.

First and foremost, a good backend technology will be scalable. It handles increasing users and data without becoming bogged down or slow.

Another important characteristic is extensibility. A good backend technology will allow new features and functionality to be added easily without disrupting the existing codebase.

Finally, a good backend technology will be robust and reliable. It withstands heavy usage and traffic without crashing or experiencing any major issues.

What comes under the tech stack for backend development?

Data analysis and data analytics are closely related concepts, with data analytics being an extension of data analysis. Here’s how they are connected:

Data Analysis: Data analysis refers to examining, inspecting, and interpreting data to uncover patterns, trends, and insights. It involves applying various techniques and methods to understand the data, identify relationships, and derive meaningful conclusions.

Data analysis focuses on exploring and summarizing data to understand its characteristics better and extract relevant information.

Data Analytics: Data analytics encompasses a broader scope and builds upon data analysis. It involves applying advanced techniques and algorithms to large datasets to extract insights, make predictions, and take data-driven actions.

Data analysis forms the foundation of data analytics. It involves the initial exploration and examination of data to understand its structure and relationships.

Data analytics further analyzes data by employing advanced statistical and analytical techniques to extract more profound insights, perform predictive modeling, and support decision-making processes.

Choose From Our Hiring Models

With us, you can choose from multiple hiring models that best suit your needs


Dedicated Team

(also known as product engineering teams)

It is an expert autonomous team comprising of different roles (e.g. project manager, software engineers, QA engineers, and other roles) capable of delivering technology solutions rapidly and efficiently. The roles are defined for each specific project and management is conducted jointly by a Scrum Master and the client’s product owner.

  • Agile processes
  • Transparent pricing
  • Monthly billing
  • Maximum flexibility
  • Suitable for startups, MVPs and software/product companies

Team Augmentation

(also known as team extension or staff augmentation)

Suitable for every scale of business and project, team augmentation helps add required talent to you team to fill the talent gap. The augmented team members work as part of your local or distributed team, attending your regular daily meetings and reporting directly to your managers. This helps businesses scale immediately and on-demand.

  • Scale on-demand
  • Quick & cost-effective
  • Monthly billing
  • Avoid hiring hassles
  • Transparent pricing

Project Based

(best suited for small-mid scale projects)

Fixed Price Model:When project specifications, scope, deliverables and acceptance criteria are clearly defined, we can evaluate and offer a fixed quote for the project. This is mostly suitable for small-mid scale projects with well documented specifications.

Time & Material Model:

Suitable for projects that have undefined or dynamic scope requirements or complicated business requirements due to which the cost estimation is not possible. Therefore, developers can be hired per their time.