A quick look at today’s corporate and commercial sector, and you are bound to come across the term Data Science or Data Analytics more than once. This is simply because Data has become a vital component of any successful 21st-century organization.
Data Science is a field in Information Technology that focuses on extracting insights from Data (Structured and Unstructured Data) and applying the knowledge and actionable insights in solving problems.
On a complete walkthrough of this article, you will gain a decent understanding of Data Science along with its needs and applications, key steps, and skills involved in the Data Science Project and come across the top 10 successful Data Science Companies.
What is Data Science?
Data Science is an interdisciplinary field that combines Statistics, Computer Science, and Machine Learning techniques to extract insights from Structured and Unstructured Data. It has one of the decade’s fastest-growing, most complex, and well-paying careers.
Upon understanding its importance, numerous Data Science Companies have emerged to provide data-driven solutions across industries. Here are two reasons why a non-data-driven company should consider utilizing Data Science:
- Data Science has strong tools that assist us in extracting insights from historical data. It aids in optimizing the business, hiring the right people, and generating more money by enhancing your decision-making capabilities.
- It helps with better business strategies by creating and advertising products by arrowing the target market. Also, consumers can use data science to find better products, especially on e-commerce websites with a data-driven recommendation engine.
Key Components of Data Science
Most data science companies follow a similar pattern when proceeding with a data science project.
Step 1: Data Exploration
Data exploration is the most crucial step, taking up around 70% of the project’s duration. The most important component data is rarely present in a well-formatted way. It often contains a significant amount of unnecessary data, called noise. Thus, this process entails sampling and transformation of data to remove the noise present.
Step 2: Data Modelling
The second step includes fitting data into Machine Learning Algorithms. The model is chosen based on the type of data selected and the business requirements to be fulfilled.
For example, the model chosen for proposing an article to a consumer will differ from the model necessary for estimating the number of articles sold on a given day.
Step 3: Testing the Model
This is a very important step for Data Science Companies as the model’s accuracy is found at this stage. The model is tested with Test Data to ensure that it is accurate and has other desirable properties. Then, necessary changes are made to the model to achieve the intended result. If we do not achieve the requisite precision, we can return to Step 2 (Data Modelling), choose an alternative model, repeat Step 3, and select the model that produces the best results for the business.
Step 4: Deploying Models
The model that provides the best result based on test findings is completed and deployed in the production environment.
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Top 10 Successful Data Science Companies
The Data Science Companies listed below are amongst the best companies for Data Science services.
1) MuSigma
With a Unicorn status in the United States, MuSigma is amongst the world’s largest pure-play Big Data Analytics and Decision Sciences companies. Through a unique ecosystem that brings together People, Processes, and Platforms, MuSigma collaborates with over 140 Fortune 500 firms.
There are currently 3500 Data Scientists working for them around the world. MuSigma has been named Walmart’s Supplier of the Year on four occasions, as well as Microsoft’s preferred Analytics partner. Thus, it is one of the top companies for Data Science around the globe.
For further information on MuSigma, visit the official website here.
2) Fractal Analytics
Fractal is one of the most well-known Artificial Intelligence and Data Science Companies. Fractal’s objective is to employ AI and help the world’s most admired Fortune 500 firms by powering every human decision in the enterprise.
Qure.ai, which helps radiologists make better diagnostic decisions, Cuddle.ai, which helps CEOs and Senior Executives make better tactical and strategic decisions, Theremin.ai, which helps investors make better investment decisions, and Eugenie.ai, which helps find anomalies in high-velocity Data, are all Fractal products.
For further information on Fractal Analytics, visit the official website here.
3) Bridgei2i Analytics
BRIDGEi2i is a trusted partner for businesses all around the world for driving digital transformation efforts. They solve difficult business problems with contextual AI-powered insights and achieve Digital Transformation results.
For further information on Bridgei2i Analytics, visit the official website here.
4) Tiger Analytics
Tiger Analytics is breaking new grounds in how AI and Analytics may be used to solve some of the world’s most difficult problems. For several Fortune 500 organizations, they have created custom solutions based on Data and Technology.
They have offices in numerous cities across the United States, the United Kingdom, India, and Singapore, as well as a large worldwide virtual workforce.
They’ve won numerous honours, including being named a Forrester Research Leader and Financial Times’ fastest-growing IT businesses. They routinely appear on lists of the “Best Analytics Firms”. Thus, they can be considered one of the best Data Science Organizations to work for.
For further information on Tiger Analytics, visit the official website here.
5) LatentView
LatentView Analytics is one of the prominent worldwide Analytics and Data Science Companies that help businesses achieve Digital Transformation and build a competitive advantage through Data. With Analytics Solutions they provide a 360-degree perspective of the digital consumer, power Machine Learning capabilities, and aid AI ambitions.
Predictive Modeling, Marketing Analytics, Big Data Analytics, Advanced Analytics, Web Analytics, Data Science, Data Engineering, Artificial Intelligence, and Machine Learning Applications are just a few of the areas in which they excel.
For further information on LatentView, visit the official website here.
6) Absolutdata
Absolutdata, an Infogain company, combines cutting-edge AI and Machine Learning with its legacy in analytical frameworks, business expertise, and technology to create scalable business impact throughout the enterprise.
The enterprise-focused NAVIK AI Platform combines AI, Data, and Analytics to serve as the intelligence layer for forward-thinking businesses. The NAVIK AI Platform provides a range of pre-built AI solutions, or it can be licensed and modified using a strong bench of Data Scientists and Engineers.
For further information on Absolutdata, visit the official website here.
7) Innovaccer
Innovaccer Inc is a leading Healthcare Data activation platform firm that uses cutting-edge Analytics and transparent, clean, and accurate Data to deliver more efficient and effective Healthcare.
Innvoaccer’s goal is to help medical-related organizations make powerful decisions and achieve strategic goals based on key insights and predictions from their data by simplifying complex data from all points of care and streamlining the information.
It is the only company amongst the top Data Science Companies which only focuses on Healthcare Solutions.
For further information on Innovaccer, visit the official website here.
8) TEG Analytics
TEG Analytics is a Data Science as a Service Company that helps businesses make better decisions by combining Business, Technology, and Applied Mathematics. Their goal is to provide Insights at Business Speed, hence, being an excellent Data Science Organization.
TEG aids market leaders in defining Analytics-driven strategy across industry verticals (such as Retail and Consumer Packaged Goods, and Healthcare). TEG has carved out a position for itself in the field of Sales and Marketing Analytics.
For further information on TEG Analytics, visit the official website here.
9) Teradata
Teradata is a Multi-Cloud Data platform that helps businesses solve Data challenges from start to finish. Only Teradata gives you the flexibility to handle today’s enormous and mixed Data workloads, making your Data more accessible to everyone without putting your Data in danger.
For further information on Teradata, visit the official website here.
10) Impact Analytics
Impact Analytics creates AI-powered retail automation technologies with a 360-degree view to help businesses automate complex procedures and turn Data into insights.
To create solutions that lure clients, they combine business expertise from top-tier strategy consultants, advanced Machine Learning techniques from skilled Data Scientists, and cutting-edge product development from expert Application Designers and Developers.
For further information on Impact Analytics, visit the official website here.
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Understanding the Applications of Data Science
All Data Science Companies provide their expertise in every industry, but the main areas where Data Science techniques are being used are:
- Marketing: Marketing has a lot of potential; for example, a better pricing approach. Data Science-driven pricing can help companies like Uber and E-Commerce enterprises increase their profitability.
- Healthcare: Wearable Data is being used to monitor and prevent health issues. The information gathered from the body can be utilized in healthcare to avoid future disasters.
- Banking and Finance: Data Science can be used in the Banking sector. Fraud Detection is one of the well-known applications in this sector, which can help banks lower their non-performing assets.
- Government Policies: Government can use Data Science to better design policies that cater to the interests and desires of the people, based on Data obtained through surveys and other official sources.
Conclusion
This article helped you understand Data Science and provided a handy list of successful Data Science Companies. As you learned the first step in implementing any Data Science algorithm is integrating the Data from all sources.
Explore our guide to data analytics companies and find out how they can help transform your data into actionable insights.
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Data Science Companies related FAQs
1. Is Data Science booming?
It is booming as the demand for data science professionals is increasing, and data has become a core decision-making influencer in today’s business world.
2. Will AI replace data scientists?
Today, AI can automate most of our tasks using Data Science, but it can never fully replace a Data Scientist.
3. What are the skills needed by a Data Science Professional?
All Data Science Companies expect the ideal candidate to know the following skills:
1. Statistics and Probability
2. Programming Skills
3. Data Visualization Skills
4. Machine Learning and Deep Learning
5. Communication Skills
Harsh is a data enthusiast with over 2.5 years of experience in research analysis and software development. He is passionate about translating complex technical concepts into clear and engaging content. His expertise in data integration and infrastructure shines through his 100+ published articles, helping data practitioners solve challenges related to data engineering.
