Big Data

A number of siloed organizational systems generate data that are distinct, independent of one another and stored in different formats. The surmounting volume, variety and velocity of enterprise data render them complex and difficult to be analysed. In most cases, the gap between analytical and operational processes is widening, especially when raw data are matched with legacy analytical methodologies.

For businesses to make the most of available data, it is essential to harmonize, engineer, cleanse, and manage them effectively with the most cutting-edge technology. Knowing this, we engineer data sets to exploit big data opportunities to unravel niche insights. We harness most current big data tools and technologies to transform data and cut the time-to-insights for decisions makers, customers, and employees.

Our Competencies

In today’s digital economy and data-driven world, businesses are seeking greater access to data flexibility to drive innovations. Moreover, leaders are differentiated by their capability to use data to create value. We use the right techniques and tools to gather any type of data and cut the time-to-insights for decisions makers, customers, suppliers, and employees.

Data Modeling Data Modeling

Organizations use a wide variety of applications, databases and NoSQL stores, making data that emerge from them incompatible and complex for data analysis. Our data modelers work with businesses to build a comprehensive data model that encapsulates the concepts of an organization and enables them to handle data as a resource, integrate information systems, and design data repositories.

Data Lake Design Data Lake Design

Traditional storage and analytic solution add to the complexity of ingesting and storing data. With data lake architecture, data scientists and analysts can do any type of processing – real-time or batched and make sense out of data at a good clip. So, whether you are looking for a data warehouse implementation or are looking to extend your existing warehouse, our data lake architecture can help you store all types of data – sensor, clickstream, web extracts, social media, relational, structured internal, documents -- in its native format and perform faster data analysis.

Data Governance Data Governance

Our data governance framework enables organizations to manage the overall usability, availability, security, and integrity of data assets within an enterprise. This enables companies to quantify the business value of data governance in the form of improved customer service, greater revenues, reimagined business processes and improved compliance with regulatory requirements.

End-to-End Data Management End-to-End Data Management

Our holistic data management service enables businesses to manage the full data lifecycle from transformation and processing to storage. This enables businesses to unravel insights for today and find solutions for tomorrow.

Custom Application Development Data Lake Design

Plug and play solutions save time and cost but not for niche players. We help businesses in developing custom big data applications and solutions with the right technology and on the right platform to fit your line of business.

Our Approach

Gather

Gather

Discussions with various department heads/core users handling different modules.

Propose

Present findings, impact analysis and suggests possible solutions.

Gather
Analyze

System Analysis

Database analysis, system performance and resource usage

Testing

Prepare test plan, case, and test data. Perform user acceptance testing and system integration testing.

Testing
Design and Development

Design and Development

Implementation of BI model for a specific use case.

Realize

Additional development effort for customization. Complete deployment into production systems along with24/7 monitoring and maintenance.

Realize
Artificial Intelligence
Data Science
Intelligence of Things

Technologies

  • python
  • rlogo
  • apache-spark
  • strom
  • kafka
  • flume
  • Tensor Flow
  • PyTorch
  • kudu
  • redis
  • cassandra
  • apache-hbase
  • Elasticsearch
  • Docker
  • Cloudera Impala
  • hadoop
  • hive
  • apache-pig
  • tableau
  • tech_DB
  • graphx
  • Plotly
  • Kibana
  • Power BI
  • amazon-web-services
  • azure
  • SAP-leonardo
  • ibm-watson
  • WSO2
  • MuleSoft

Building a successful data model is often a step-by-step process. Our data modelers work with key stakeholders in an organization for defining and analysing the data requirements that underpin the key business operations. After this phase, we build a conceptual schema and hold discussions to ascertain the concepts of an organization and the relationship between data. This is then translated into logical data model and subsequently into physical model that organizes data into the required format for easier data management and its analysis.
Our model-driven data services include:

  • E-R modeling
  • Strategic data modeling
  • Dimensional modeling
  • Business modeling

Organizations spend too much time gathering and preparing their data, which in turn lengthens the time-to-insights for critical decision making. We follow a three-pronged strategy -- Analyze, Measure and Improve -- to study your data and current data management processes, identify technological flaws associated with current analytics solution, bring to light counterproductive workflows, and formulate analytics solutions to transform data for improving the pace of your decision making processes and optimizing your business processes.
We help organizations in:

  •  Technology Audit
  •  Assessment of current data management environment
  •  Executive Training to sync workforce with new big data technology
  •  Building roadmap for data management and predictive analytics solution

Any data - be it structured or unstructured - have a unique set of attributes, metadata, structure, and schema associated with it. Integrating such data from disparate systems add complexity to data integration projects. Moreover, multiple interfaces between applications also create inconsistencies and duplications. With our data integration services that cover seamless real-time data migration, transformation, mapping, synchronization, and data management, we help organizations get a unified view of data without disrupting their critical business processes.
Our services cover

  • Data Import and Export
  • Data Replication
  • Master data management
  • Data synchronization
  • Data governance

Organizations are flooded with data - from multiple internal and external sources - which play a vital role in maximizing the revenue, minimizing the cost, improving the customer satisfaction and mitigating the risk. It is vital for organizations to share, store, secure and retrieve the data most optimally. Our Enterprise Data Management service enables organizations to manage the end-to-end processes in data transformation from data acquisition, data storage to information delivery.
Some of the key data management offerings are:

  • Data Migration
  • Data Quality
  • Data Modelling
  • Data Cleansing & ETL
  • Data Maintenance & Meta Data Management

Today's data-driven business demands cannot be met by traditional big data architectures that seamlessly move data from production systems to data warehouses. Only a well-planned data architecture schema can help in realizing improved profits and lowering risks from an otherwise opaque data. Our data scientists assess the data type, frequency, size, processing methodology, data source, and hardware requirements to create a unified information architecture that supports your line of business. Our big data architecture covers:

  • Data consolidation and integration
  • Analytics 
  • Process mapping and automation
  • Governance
  • Quality of service protection to preserve data quality and compliance

The real value of big data can be unlocked only when insights obtained from data sets are put into daily practice across departments and industries. Businesses can use data to offer their customers a highly personalized product or service recommendations so that users have to spend less time trying to figure out what to buy. Big data can also help businesses improve productivity by automating mundane tasks, resolving probable issues, optimizing business processes, mitigating risks and detecting fraud. See how data can add value to your business.

Retail
Retail
  • 360-degree view of customers to understand customer behaviour
  • Measure brand sentiment to understand the popularity of a product and for targeted promotions
  • Improve product placement and store layout for in-store personalization and shopping habits
  • Improve ecommerce website performance with social media activity and purchase history
Fashion
  • Market basket analysis and recommendation engine based on past shopping data
  • Successful order fulfillment with real-time inventory management and tracking
  • Customer segmentation based on predicted buying behavior
Fashion
CPG
Wholesale
  • Efficient supply chain management with data providing greater transparency to carriers, suppliers and customers
  • Improve demand supply visibility – Real-time Predictive Analytics for demand supply visibility and automated demand-supply balancing
  • Improve profitability – Automation of warehouses and supply chain
  • Supply route optimization with data from sensors on delivery vehicles, weather data, and road maintenance data.
CPG
  • Build a product marketplace that resonates with consumers’ tastes
  • Sourcing and procurement analytics to empower buyers with the best combination of goods, vendors, and services
  • Demand forecasting to meet consumer needs based on point of sales and consumption data
Wholesale
life science
Life Science
  • Prediction of treatment outcomes by correlating phenotypic, genotypic, EMR, clinical and other types of data
  • For fraud detection and checking legitimacy in claim handling
  • Ensure wellness of patients by monitoring vital signs
  • Improve public health by analyzing disease patterns and tracking disease outbreaks

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