Data science platforms are a type of software that combines multiple data sources, cleans them up, and organizes them in an intuitive way. This makes it easier to find trends and patterns in data sets—and provides insights from multiple sources at once.
For businesses, these platforms pave the way to different applications that can drive growth. Data science can offer customer insights, increase security, and guide internal finance decisions.
Along with data transformation tools, these platforms are among the most innovative solutions that are changing the industry today.
Data science platform definition
It is software that helps you combine and analyze data from a variety of sources. Data scientists use these platforms to aid data mining by analyzing, predicting, and automating tasks that would otherwise be too time-consuming.
Data science platforms can be used in many different ways: by businesses, governments, or individuals.
Data science platforms are generally used to build models that can make predictions about new data sets based on historical information about what has already happened or supervised learning.
When does your company need a data science platform?
Data science platforms are useful for any company that wants to combine data from multiple sources, analyze data from a variety of sources, and visualize their data.
Here are some signs that your business could use the help that data science platforms can offer:
Your process needs fine-tuning
It is important not to ignore signs of work process friction points, especially ones involving unity and structure systems. A Salesforce study found that ineffective collaboration and communication is one of the key drivers of business failures.
For organizations struggling to develop a coordination strategy, a data science platform can help provide a centralized way to work on projects and provide greater visibility.
It’s getting more challenging to hire
It’s expensive and exhausting to replace employees. Employee turnover is one of the biggest reasons companies struggle to hire—and retain—new talent. From lost productivity to hiring costs, it all adds up.
Supplementing a team with a value-rich platform can help maintain productivity regardless of staffing issues. It can cover data science tasks such as data preparation, monitoring, and model testing.
Your team is overwhelmed
With the shifting job market and the greater demand for data, a team of scientists can suffer from strain and not maximize their full potential.
A data science platform can help streamline data preparation and allow your team to alleviate the unnecessary burden in their workflow.
Not waiting until your team is overburdened with pending deliverables before integrating a platform into your operations also helps avoid the speed bumps that your company may encounter.
Advantages of using a data science platform
Data science has changed the way we do business. It can aid businesses across different functions, such as sales and finance. There are many benefits of data science and reasons why you shouldn’t ignore its use in your life.
Drives team collaboration
Working with data involves complex processes such as knowledge base management and reporting of findings. These tasks involve accuracy and, at the same time, effective communication to ensure a smooth process and data access.
Data science platforms that run in the cloud offer many benefits, including unlimited storage, a managed service environment, and integration of collaboration software.
A data science tool can help your business make informed decisions based on structured predictive data analysis, reducing wasted time and resources. These platforms also enable automation which helps speed up response times and reduce human error, as found by a study.
They provide a way to view data in real-time, producing results and allowing more agility for business leaders. This can be done by using dashboards or projections made possible by a data scientist’s data treatment.
Offloads low-value tasks
Data science platforms take care of many of the tasks associated with data science operations, allowing data scientists to focus on developing better output and strategies.
The leading data science platforms have the potential to improve the time it takes to accomplish labor-intensive tasks such as experimentation and research.
Best data science platforms to try
The top data science platforms can help companies drive productivity through model delivery, artificial intelligence, and other cutting-edge technologies. See a quick overview of the options below.
Dataiku was founded in 2013 as an artificial intelligence and machine learning company. It provides a cloud platform for teams to create and deliver data and advanced analytics.
The company offers a means to customize, reuse, and share code, resulting in a streamlined production process.
Kaggle was founded in 2010. It offers a platform where people can discover and publish data sets, build models and collaborate with other data scientists and machine learning engineers.
Users can access over 50,000 public datasets and 400,000 notebooks for different analysis projects.
Alteryx is a computer software company in Irvine, California. The company’s data science and analytics products are available in desktop and browser-based models. Alteryx makes advanced analytics accessible to ordinary people. It offers users a 30-day free trial.
Data science platforms help you combine and analyze data
The best data science platforms provide a great way to combine the data from your company with other sources and analyze it in an easy-to-read format.
They also give you more power over what data is stored and how it’s used, which can be very useful when working with sensitive information like credit card numbers or medical records.