To add to the unreasonable power of Plot.ly, Plot.ly also supports several different types of statistical plots. Further

Both roles vary from company to company. What stays the same are the goals and impact that each role employs. Perhaps the biggest difference is the method of how you get to the solution or surface a finding. Some Business Analysts may find themselves eventually becoming Data Scientists, and vice versa. It depends on your preference for the skills and tools needed to perform your job.

Thank you for reading! I hope you found this article both interesting and useful. Feel free to comment down below some of the similarities and differences you have found or experienced between Data Science and Business Analytics.

On top of all of that, Plot.ly also has some lesser-known charts and graphs that you would be hard-pressed to find in most other data visualization packages. Funnel charts, pie charts, violin charts, and tree maps are just a few examples of some unique and fun ways to explore data using the Plot.ly library.

Thank you for reading! I hope you found this article both interesting and useful. Feel free to comment down below some of the similarities and differences you have found or experienced between Data Science and Business Analytics.

Of course, there are some key differences between these two roles. One of the biggest differences is the use of Machine Learning for Data Scientists only. Another difference is that a Business Analyst can expect to communicate more to stakeholders than a Data Scientist would (sometimes Data Scientist work can be more heads down and not involve as many meetings). Here is a summary of the differences you can expect to find between these positions.

To start us off, I am going with a library for data visualization that is pretty well-known, but some might have never heard of. Plot.ly is a graphing library that takes interactivity to a whole new level. I would genuinely advise using Plot.ly over something like Matplotlib or Seaborn. This is because Plot.ly comes with a multitude of different tools that most scientists can certainly come to appreciate. Just how much is in Plot.ly?

On top of the beautiful styling for basic plots, Plot.ly comes with a fully-featured 3D visualization system that rivals some of the best available with modern technology. One great advantage to the way that Plot.ly handles 3D is performance. Although 3D visualizations are of course quite complex and intensive, Plot.ly seems to handle a lot of these applications with relative ease. 3D visualizations are also awesome because the new axis allows for a greater amount of understanding by exploring data’s positional values in 3D space. Furthermore, the Z axis can also represent a variety of features — making it possible to view several different correlations at once.

Although the financial side of things is certainly not where most of my domain knowledge falls, Plot.ly has great support for several financial visualizations. This goes to show Plot.ly’s versatility as well, as visualizations rely both in and out of many scientist’s domain. Like everything in Plot.ly, financial charts are easy to use and beautiful — a while ago I worked on a project where we tracked the value of currencies and created a full web-app with an LSTM model that would retrain itself and predict new data based on what it had learnt. Plot.ly really came in handy with its easy to use and Javascript integrated visualizations for candlestick data in this circumstance.

It is hard to argue with Plot.ly’s beautiful approach to maps, as well. Plot.ly’s clorepleths in particular are an absolute joy to use and can make compelling visualizations in a matter of seconds.

One thing that has become surprising in the recent development of technology is geo-data. Geo-data has evolutionized with FIPS to such an extent primarily because of smart-phones and global positioning systems (GPS,) and this has given way to a strong foundation for data science to build on top of. This is of course because data is now more readily available than it ever has been for free with geo-data included.

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ification of certain serious long-term neurological conditions is possible by monitoring subtle changes to speech. This can be done without hospital visits or even without targeting those who are at risk. Conveniently for all concerned, we all speak into our phones and computers all the time, so it would only be necessary to opt in, and give permission for your voice to be analysed, without compromising confidentiality by being recorded or listened to.

Plot.ly comes preloaded with all of the fantastic tools that your average data scientist or even just computer programmer might expect. Scatter plots, bar charts, and line charts are all staples of the Plot.ly module. While Matplotlib can accomplish similar goals, Plot.ly has the same functionality while also having default styling and Java-script interactivity that makes it a lot more fun and a lot easier to explore data. On top of that, presentations are certainly a thing that could be served a benefit from using Plot.ly over many of its competitors.

These two roles share goals with one another. Each requires a deep dive into data with similar tools as well. The process of communication is similar, too — working with stakeholders from the company to go over the business problem, solution, results, and impact. Here is a summary of the key similarities between a Data Scientist and a Business Analyst.

Of course, Python is also the most popular programming language used today for data science. While most scientists working with the language might be familiar with a lot of well-known and widely used packages such as Scipy, Sklearn, and Matplotlib, there are some packages which most data scientists have never even heard of that are also quite awesome!

The most popular general purpose programming language on planet Earth right now is the Python programming language. This is not only because Python is incredibly easy, and relatively fast, but also that Python has a killer ecosystem with tools to fit every discipline from business to finance and science. One area that this is certainly proven to be true is in the wonderful world of data science.