How Does Data Science Work?

Data science is a field that uses a wide array of scientific methods to gain insights and extract knowledge from data. Data scientists take raw data and refine it using sophisticated techniques and expertise in various disciplines.

A data science team must be skilled in various fields such as mathematics, engineering, computing, visualizations and statistics.

This expertise allows them to extract useful insights and information from massive volumes of data. This data can consist of your business’s most crucial bits of information.

Hence, data science helps drive innovation and decipher new opportunities.

Data Science Process Life-Cycle

Capture

The first step of data science deals with how data is collected. Data is always distributed across various business applications and systems; it is never in one place. New data can also be entered into a system, which can either be manual or automated.

Maintain

This step deals with what happens to the data once it is sourced. The process of data warehousing stores data collected from different sources. Then, inaccurate, unreliable, duplicate and missing data is removed from the database.

Process

Data mining is used to identify trends and future patterns in a data set. Processed data is then classified based on similar traits. This data is used to produce a descriptive diagram showing the relationship between different data types.

Analyse

After classifying and modeling the data, the next step is to analyze the data. Using data analytics can help make predictions based on the data. It can also be analyzed using regression, text mining, and qualitative analysis methods.

Communicate

It is essential to display the results of your analysis to gain utility from the data. This can be done using reports consisting of the results of research and analysis of the data.

What Do We Provide In Our Data Science Consulting Services?

We provide end-to-end data science services to help you get value from your data. Just share your data and we will handhold you to decipher it. Our data science experts make sure you are not just knowing the data but making better decisions from it. Our team ensures that you know the best algorithm or model to use and allows you to choose the right platform that suits your needs. With our data science consulting, you can get the right answer to your business questions.

Strategy Building

Automating the documentation of data is a huge step in the direction of creating a holistic data strategy. Our data science experts ensure that the data delivered is usable and can generate real-world results. This allows our clients to make better decisions. We plan each stage of the work and allow our customers to procure data in the right way, convert it into manageable chunks, and then apply the different data science techniques to deliver valuable, automated, and predictive insights to our customers.

Validation Of Strategy

Our experts lead our customers through a series of easy steps to get them started and allows them to understand and assess the problems at hand and offer solutions based on the strategy built by running it through different models and evaluating them by testing each data set. It not only allows us to check the functionality but also makes sure that it adheres to the prescribed demand of the clients.

Model Development

Development of the model is about deciding which algorithm or machine-learning model we will use based on the requirements and demands of the situation at hand. Since only a few of the algorithms apply to certain situations, our data science experts make sure to use the right algorithm to ensure optimal outcomes.

Benefits Of Data Science Consultancy

Our data science consultancy will help you understand use cases in your process where we can assist you with data-backed insights. We offer customized data science solutions that can work with your proprietary data and integrate it into your workflow. Our lean and agile team of full-stack data scientists, engineers and application developers accelerates the innovation and implementation of data-driven solutions. As a data science services company, we bring extensive cross-industry expertise backed by scientific rigor and deep knowledge of state-of-the-art techniques to design, build and deploy bespoke data solutions.

Increase Sales

With data-driven insights provided by our experts, you can not only assess and manage your data but can also take meaningful and effective decisions based on real-world insights and can make changes in the process management which allows you to stay ahead of your competitors and can, in turn, increase your sales output. These insights allow you to identify your target customer and can help you in creating more value for your products and solutions for your customers.

Enhance Efficiency

Using advanced analytical tools of data science provides insights related to their customer behavior which allows companies to make better decisions and increase their revenue. These tools can help in the analysis of the competitors, market conditions, evaluation of surveys, and making product/service recommendations. Data science can help in gaining knowledge by processing large amounts of data quickly and efficiently and allows businesses to enhance their efficiency and performance.

Manage Risks

Data science provides deep and meaningful insights which allow analysts to explore, identify and mitigate risks from various perspectives. It also helps in predicting certain outcomes and can help in avoiding potential hazards and future risks by evaluating the quality of the existing process and assessing and updating them to avoid future risks.

Transform Your Business

Data science tools offer in-depth insights and real-time access to the data which allows businesses to make better decisions, optimize their internal processes and support better decision making. Making better decisions and optimizing the processes, expands the flexibility and also leads to reduced costs.

Data Science Guide 2022 | MindBowser

Free Data Science eBook – A Complete Guide

This ebook will answer all your questions about data science and how to put it to use for your business.

Why Does Having A Data Science Partner Make Sense?

Given the shortage of data scientists and the dispersed range of skills required to execute a data science problem, it is often hard to build a data science team for most companies. Here is how Mindbowser can build a data advantage for you quickly.

In house vs Data Science Company | MindBowser

Meet Our Data Scientist

Sandeep Natoo

Head Of Emerging Tech

Sandeep is a certified, highly accurate, and experienced Data Scientist adept at collecting, analyzing, and interpreting large datasets, developing new forecasting models, and performing data management tasks. Sandeep possesses extensive analytical skills, strong attention to detail, and a significant ability to work in team environments. Sandeep has 12+ years of experience in building software products and juggling with data.

He has been known for translating complex datasets into meaningful insights, and his passion lies in interpreting the data and providing valuable predictions with a good eye for detail. He is highly optimistic and an avid reader.

Here Is What Our Customers Say About Us

Apply The Power Of Data Science To Your Business Process Without Code Or Data Scientists

We are a team of adept data scientists who have an excellent track record of generating great value and return on investment for our clients. As a data science services company, we implement a holistic approach to data, planning each stage of the work and aligning it with your vision. We help our customers procure data in the right way, convert it into manageable chunks, and then apply the different data science techniques to deliver valuable, automated, and predictive insights to our customers.

Our data science consulting process is about leading our customers through a series of easy steps to get started on their data science journey. We start by understanding the problem at hand, getting the stakeholders together, assessing the data, running it through data models, and providing insights to the customers.

Data Science Services | MindBowser
Data Science Services | MindBowser

Data Science Service Offerings

We offer end-to-end data science services to help you get value out of your data. Just share your data and we will handhold you to decipher it.

Data Preparation

Enriching the data preparation processes by missing value replacement, outlier analysis

Model Generation

Generating, testing, and refining model-based data on the validity of the output

Migration

Migration of algorithms, models from one platform to the other, e.g., SAS to R

Consulting

Appropriate scope identification, feasibility assessment

Check Out Our Successful Data Science Solutions And How We Delighted Our Customers

Our Expertise In Data Science

With the support of advanced technologies, we help you get the most out of data.

Explore Our Capabilities

As a data science service provider, our team will help you understand use cases in your process where we can assist you with data-backed insights. You do not need any learning curve or hire costly data scientists anymore. We offer customized data science solutions that can work with your proprietary data and integrate it into your workflow. Additionally, all data is worked under secure access and stringent NDAs.

Data Collection
  • Structured & Unstructured
  • Semi-structured
  • Distributed File System
  • RDBMS & Big Data
  • Emails, Websites & Web APIs
  • Flat file (text, CSV, JSON, logs)
Data Processing
  • Data Cleansing and Profiling
  • Normalization, Text Mining
  • Data Transformation
  • Data Extractor
  • Load Data to Data Warehouse
Feature Engineering
  • Principal Component Analysis
  • Locality Sensitive Hashing
  • Singular Value Decomposition
  • Vectorization, Indexer
  • Text Transformation (word2vect)
  • Feature Scaling
Optimization & Evaluation
  • Cross-Validation
  • Gradient Descent, SGD
  • Hyperparameter Tuning
  • Ensemble & Boosting
  • Log-loss, F-measure, Precision-Recall
  • RSS, RSME, MSE
Machine Learning
  • Regression Algorithms
  • Classification Algorithms
  • Support Vector Machine (SVM)
  • KD-Tree, Decision tree
  • K Nearest Neighbors (KNN)
  • K-means, Latent Dirichlet Allocation
Deployment Processes
  • Model Deployment
  • Model Pipeline
  • Model Serving
  • Managed Deployment
  • Monitoring and Evaluation

How To Execute A Successful Data Science Strategy?

Even though data science is rapidly gaining popularity among businesses and IT leaders, many companies are having a hard time implementing and executing their data science strategies. The following steps will help you effectively execute your data science strategy:

Build An Effective Team

Create a stable team consisting of multiple talented individuals rather than a team of one or two experts who can do it all.

Identify Key Business Drivers

Understand why your company needs data science and how it can contribute to the success of your business.

Protect Your Valuable Data

Implement governance policies to ensure the security of sensitive data during data science implementation processes.

Emphasize On Articulation

The insights provided by data science analytics are of no value unless their value can be properly articulated.

Improve Data Processes

Your team should focus on reducing the time to develop and deploy the new analytical model.

Tools And Technologies

As data science service providers, our experts put statistical and mathematical methods and tools to invent solutions that help companies automate processes, optimize out-and-out operation processes and add extract business value with data.

Industry

We work with all-size businesses— from startups to Fortune500— in industries from engineering and tech to pharmaceuticals, retail and energy.

App Strategy & Consulting
Finance & Insurance
App Strategy & Consulting
Transportation
App Strategy & Consulting
Real Estate
App Strategy & Consulting
e-Commerce
App Strategy & Consulting
Pharmaceuticals
App Strategy & Consulting
Lead Generation
App Strategy & Consulting
Media
App Strategy & Consulting
Tourism
App Strategy & Consulting
Manufacturing & Engineering
App Strategy & Consulting
Digital Healthcare
App Strategy & Consulting
SaaS
App Strategy & Consulting
Research

Why Mindbowser For Data Science Services?

Our lean and agile team of full-stack data scientists, engineers and application developers accelerates the innovation and implementation of data-driven solutions. As a data science services company, we bring extensive cross-industry expertise backed by scientific rigor and deep knowledge of state-of-the-art techniques to design, build and deploy bespoke data solutions.

1

SOLUTION ACCELERATORS

Ready models that result in time and cost-saving

solution accelerators
2

DOMAIN EXPERTS

We help you identify & validate viable use cases across your business, guide your model through to deploying your models into production

domain experts
3

IN-HOUSE EXPERTS

A strong team led by Ph.D. holders in data science and AI

In-house experts
4

360 DEGREE SERVICE

We cover the full spectrum of ML and AI that is required to get the right ROI for your business.

360 degree service
5

FRAMEWORK AGNOSTIC

Our solutions are independent of the framework. You can continue to explore proprietary tools as well as choose among open source options

Framework Agnostic

Frequently Asked Questions

What is data science consulting?

As a leading data science consulting, analytics and implementation services company, we take the time to understand your requirements in detail, offering a data science methodology that is customized to support your needs. We would apply our data science methodologies to both the analytic and implementation aspects of your project.  We will provide you with much-needed business insight, statistical rigor and predictive power, with the ability to automate your workflows, and transform your organization. The inputs enable you to apply the data in a prescriptive or predictive manner, depending on your requirements.

Why are data science consulting services important?

Data Science is a branch of advanced programming techniques that makes data more actionable. It enables new levels of data utilization, driving actionable insights. Data science can help companies in increasing their sales, improving their efficiency and optimizing risks. Data science solutions can deliver software, models and analytical tools that help C-level executives, analysts, and business users make better decisions.

What does a data science consultant do?

A data science consultant helps your business to identify and choose the data models or build a new one based on the requirements related to the problem at hand. A data scientist can use various tools and techniques available to increase the efficiency of the modeling process. They use statistical and mathematical methods and tools to invent solutions that help companies automate processes, optimize out-and-out operation processes and add extract business value with data.

How to assess a data science team?

Data science is a team sport. For assessing a team there are various metrics and KPIs that can be used. Typically a good data science team should have excellent critical-thinking skills, mathematical skills and analysis skills. They should also be able to adapt to changes quickly without much of a hassle and should have a clear goal or vision for the project given. Past experiences of the team like the number of projects completed successfully, financial metrics and the amount of time saved in operations can be a metric to define the ability of a team.

 

What are the current challenges in data science?

Here are some of the challenges that data scientists are facing in 2022

  • Cleaning and preparing the data to improve its quality.
  • Handling multiple data sources since organizations are using different tools and apps to generate and gather data.
  • Transitioning to the cloud makes the data vulnerable to cyber attacks.
  • Understanding of business problems as data problems become complex. 
  • Communication barriers between non-technical business executives and clients due to the complexities and technical jargon of their work.
  • Missing to define KPIs and metrics after understanding the requirement of the projects.
Can duplicate data be automatically detected even if it is from the same site.

We can detect duplicates based on case number, docket number, and link addresses.

How does the storage of files managed?

The documents can be stored over your AWS s3 buckets. 

What's the distinction between a one-time scrap script and a recurring script?

One-time scrape will not need any pipeline development. In contrast, recurring scripts will need pipeline development.

The pipeline development contains configuration on run frequency, filters the data, uploads the data to storage like DB, and monitors the scraper logs.

What does the deliverable/handover look like? Code? Downloaded Documents? Etc?

The deliverables will be the output file & source code.

What are the exact steps in the process for an engagement like this?

1) Share the website & the list of fields to be extracted.

2) Check the feasibility

3) Scope out the timelines.

4) After the agreement on scope, the development started.

5) Based on the deadline, the output & code will be shared.

How do we track the progress of the project?

Our developers use project management tools like JIRA, Trello, etc. If you want, we can use that to track the project. Or we can manage through an excel sheet as well.

How does Mindbowser denote project milestones?

Based on the scope of work, we divide them into tasks & every task has some deliverables that lead to milestones.

If it's a fixed cost arrangement, what happens if it runs over budget?

The fixed cost budget is calculated based on the scope of work. If the scope of work changes, the budget part also gets affected.

How do we keep accountability?

The accountability will be based on the milestones we designed.

If there is something wrong with the deliverable? Who is responsible for it?

Once the deliverables are submitted, the customer team must verify them. To verify these things, we set some days. If you find anything wrong in the verification period, Mindbowser will be responsible for fixing the issue.

What is Mindbowser's Contingency plan?

We have a pool of developers. If an emergency happens, there are other developers who will act as replacements & achieve the deadline.

We also follow some developing standards so anyone new can easily adapt them.

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