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10 top data science companies to check out in 2022

19 April 2022
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Top data science-companies-s

The data science market is growing in leaps and bounds with top data science companies chipping into the blossoming data landscape. That’s why we’ve put together a list of the best data science companies for 2022. These teams are leading the charge in Big data, machine learning, and artificial intelligence, and are poised for continued success in the years to come. Our rating is a compilation of the leader’s matrix provided by global ratings and reviews platforms.

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IBM-big
Focus: global technology services Headquarters: Armonk, New York
IBM: the true mogul of business intelligence

IBM is an American multinational tech corporation specializing in a spectrum of tech-related services. BI is one of their flagship offerings to help companies establish a data-driven strategy.

IBM has over 200 open data scientist job positions, continuing to grow the expert workforce for forward-thinking businesses. The company was named a leader in the 2021 Gartner Magic Quadrant and remains actively engaged in advancing the BI landscape. IBM manufactures and sells computer hardware, middleware, and software, as well as hosting and consulting services in a variety of fields, from mainframe computers to nanotechnology.

What is the best data science company?

The data science field is evolving rapidly, with new industries and use cases for the technology emerging every day. As businesses strive to capitalize on the insights that can be gleaned from data, they are increasingly turning to data science teams for help. Data-related development and services are an exploding field. As a result, there’s no shortage of talent there. But which team of professionals augurs well for your project?

When trying to decide which data science company is best for you, it’s important to first figure out what data science challenges you’re facing. Do you need help analyzing and understanding your data? Are you looking for help with machine learning or data mining? Or do you need a company that can help you build a model or application?

Data science

Source: Unsplash

Once you know your business agenda, shortlisting future vendors becomes easier. In any case, we’ve curated the list of the leading companies in these verticals to introduce you to the data champions, and now sharing some tips on how to choose the right vendor vendor.

How to choose the right data science company

A recent study by IBM found that data is growing at a 44x rate. This unprecedented influx is fueled by an increasing number of connected devices, which is estimated to reach 38,6 billion by 2025. Therefore, it’s hard to undervalue data science impact on forward-looking businesses. To make sense of this data and derive insights that will impact businesses, it’s essential to have professionals skilled in data science.

But not all business intelligence companies are created equal, and it’s important to do your research before working with one. Here are some tips for you to shortlist potential tech partners.

Solidify your business case

First and foremost, you should know exactly what you want from a future collaboration. Is it migrating from on-site infrastructure or structuring the scattered data bits? Or do you need timely prevention of costly downtimes? If you’re having a hard time performing audits of current operational weaknesses, you should also look for a vendor who provides consulting services.

Also, if your company already has an in-house team of data experts, it might be enough to expand your on-site capacity with outsourced talent. On the contrary, a full-scale project necessitates an experienced team of data engineers who can take over your project from ideation to delivery.

Choose the location

Tech outsourcing is now more relevant than ever. In a modern remote-friendly world, where geographical borders get erased, you have a hyper-wide choice of destinations. When it comes to where you should outsource your business functions, there are many factors to consider.

Data science project details

As a rule, US companies tend to be the most expensive, while other less-obvious destinations offer a great price-value ratio.

Set clear benchmarks for the future tech partner

Your final choice should also depend on the case-specific goals you are targeting. Unique business needs, domains, particular data science solutions should become the core factors.

Moreover, factors in general selection characteristics include:

Vendor characteristics

Other ‘soft’ skills such as stable communication, transparency, and security also contribute to a perfect vendor profile. Thus, you should focus on communication from day one. If your business vision doesn’t click, the vendor won’t be able to find the best solution for your needs.

Enter the evaluation phase

By this time, you should already have a few bids from selected candidates. It means that the salient part of the search journey is on its way. Any cooperation should start with a problem exploration to validate the need for business intelligence or AI services. To do that, your vendor should request a detailed description of your business problem and operational data to evaluate. Make sure you sign an NDA first to protect your corporate information.

The final word

Businesses now more than ever are reliant on data. The most successful organizations have robust analytics solutions and processes to have a holistic view of ongoing fluctuations and make sound decisions based on them. Therefore, data science solutions are no longer an option in the age of Big data. While there is no lack of talented professionals, it is important to choose wisely.

When choosing your tech supplier, make sure you take heed of common criteria like experience and portfolio as well as less obvious factors such as legislative proficiency and effective communication. When done properly, your organization will be able to establish a robust data wheel that will keep your business resilient in the years to come.

Let’s work on your data science project!

For more data science & other tech posts, please take a look at our blog.

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