Data Science

Data Science

Data science consulting is the process of influencing change through improving a client’s analytical abilities, establishing competencies, and comprehending the inner workings of their company. Though both data science consulting and ordinary consulting are concerned with making data-driven choices, the critical distinction is that data science consultants provide their customers with reusable operational models. On the other hand, most routine consulting assignments solve significant but one-time concerns and do not provide customers with operational decision-making models.

Data Science Service Provided By Bookmark Infotech

The strategy portion of the consulting is investigating what can be done with data and developing a strategy.

Read More Close

This section necessitates a thorough understanding of the use cases. Depending on the client's industry, the data gathering process, regulation, and objectives might all be quite varied.

The validation stage is required to ensure that the identified approach is correct. While developing a strategy

Read More Close

may be done in a matter of hours in an emergency, putting it into action might take months. As a result, it's critical to test the plan.

Designing and developing a modern data product or internal tool is referred to as development.

Read More Close

This is more along the lines of data science consulting's IT side. The creation of custom-tailored solutions for unique situations necessitates a strong focus on the development process.

The client's team's data literacy is being improved through training. This would ensure that the rest of the team

Read More Close

is aware of the process and can contribute to system improvement. This would also ensure that the team would capture the key points and contribute meaningfully to the process's continual development.


Strategy And Build Up

(Consulting, Building Algorithms, Defining Data Processes)

  • Data integration with the current solutions
  • Understanding data processes work and define data storage practices
  • Data assessment
  • Understanding business case
  • Strategies to improve the time to market
  • Capacity planning to meet the end-goals

Integration Management

(Infrastructure Configuration, Monitoring and Maintenance)

  • Configuring Hadoop clusters
  • Big Data Application Integration Services
  • Integration with existing Enterprise Data Warehouse and Data Sources
  • Building Real time data pipeline
  • Migration from Relational DB to NoSQL

Data Processing

Batch Data Processing / Real Time Data Processing

  • Collect and process gigantic heaps of data that often prove too complex to handle
  • Trend Analysis, Pattern Identification, Payroll and Billing Systems, Weather Forecasting
  • Real-time data processing by deploying the collected business data to drive insights
  • Stock Market Analytics, Real-time taxi booking
  • Serverless ETL Process Definition
  • Make scaling easier by processing high-velocity and high-volume transactions and events more efficiently and in a faster time frame
  • Orchestration using Airflow

Data Analysis
Data Presentation, Provide Actionable Insights

  • Analytics, Dash-boarding & Alerting

  • Informed decision making by leveraging BI

  • Intelligent and personalized insights about gaps and opportunities for improvement in processes

AI/Machine Learning
Analyse Hybrid Data, Foresee and Tackle Setbacks.

  • Machine Learning/Data Mining

  • Data Modelling

  • Predictive and Prescriptive Analytics
  • Analytics Optimization

Want to Know More About Our Services?


Contact Us

+91 8976-965-992


Let's Connect for Business ...

    First Name*

    Last Name*

    Your mail*

    Phone number*



    error: Content is protected !!