An Overview of Common Data Science Tools

Never before has the data sciences field been so popular. A new trend in college majors, data scientists are in high demand due to the volume of information gone digital in the 21st Century. From general programs designed to store and organize data to statistical information and scripting tools and batch processers, there are many tools you’ll need to get up and running in this field.

While you could go to school for a degree in the data sciences, others choose the self-taught route to help businesses process information, make decisions, and keep an eye on trends. Regardless of your route and how you plan to get there, here is a brief overview of some of the industry’s most important tools.

Free Student Tools

Technology moves fast and, so too, do the tools students use in the data sciences. Students all over the globe were recently told that Spotfire, a data collection tool capable of making quick sense of numbers, is now available for free for their use. TIBCO’s free academic program has IT students excited to begin number crunching and data analytics in a new way.

This particular resource will help data scientists, and now university students, to use artificial intelligence to explore new data insights important to businesses and broader fields like the sciences, research, and law alike.

Statistical Information Collection Tools

From Excel to Spark, there are hundreds of tools and programs used every day in the data sciences. This is because not only do numbers need to be analyzed, but they need to be organized in different ways to make sense to whoever is looking at them and why. For example, if a company or business needed data services to contract track or trace COVID-19, the information would then need to be compiled in various forms for presentations. If that company were to be giving out statistics and facts to the media, for example, they might want spreadsheets and graphs or a combination.

If the same data was going to the state for further tracking or so that health officials could make specific recommendations, the numbers might need to come in differently. Perhaps those numbers would need to include predictions, recommendations, and more. The more complicated the data and analysis the job is for, the more statistical tools that would be needed. Otherwise known as SAS, statistical tools for data analysis are the most important in this field as SAS is data services’ main language.

Batch Processors

For companies looking to produce large volumes of numbers with little human intervention, the reliability of data processing services and artificial intelligence used is imperative. Like with the statistical tools that work to give us information, batch processers do this in massive volumes. These software programs work to pump out numbers quickly and accurately and often work in real time. They can save companies money with mundane and routine tasks like payroll, too.

Scripting Tools

Scripting tools used in data management are the glue of the field. Designed to speak in many languages and talk to a variety of databases and servers, these tools work toward getting complicated information and code into the world in legible ways and helping numbers to make more sense. Script helps in saving time and working through complicated problems for fast analysis.

A complicated but incredibly essential field for the modern world, data science is only as good as its scientists and tools. When doing your research about what you might need to stay on top of the latest data science technology, Spotfire and other general programs might be a great place to start. As you get deeper into your studies of the field, keep an open mind on the ever-evolving options for adding more tools. The future depends on you.

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