Big data is an amazing way to get actionable insights and measurable results for your business. Of course, it’s important to know what each kind of data can do, and the best ways to handle the data that you have.
When it comes to data science and data analytics, people often act as though they produce the same information. While they do work well together, each brings its own strengths to the table and offers specific information.
So to help you out, we’ve got an easy guide to helping you distinguish between the two, and when each is most useful.
Data science is used when you’re trying to find actionable insight from larger sets of structured and raw data. In essence, it’s about finding out the answers to the things you even didn’t know you didn’t know.
A data scientist will look at computer science, statistics, predictive analysis, and machine learning in order to find the kind of solutions for problems that might not have happened yet, but that could.
The purpose of data science is to find out the right questions that should be asked, rather than focusing on getting the answers.
The result of data science will come through when looking for potential trends, comparing disparate data sources, and researching and finding better ways to analyze information to make it useful.
This information can be used by itself and is particularly handy when trying to improve AI algorithms and improving machine learning. Having carefully managed data science, you can organize a huge swathe of information. As a result, data scientists can ask the vital questions that your business needs to be aware of.
Data analytics looks more at statistics and the kinds of data analysis used to connect diverse data sources and trying to find connections between the results.
An analyst will focus on how you collect, process, and organize data in order to create actionable results.
A data analyst will also find the most appropriate way to present the data in a clear and understandable way.
Data Analysts will focus on concrete problem solving and question answering which can then lead to immediately improving the situation. Initiatives off the back of data analysis can help you to increase revenues, improve operational efficiency, and optimize efforts and campaigns. They allow you to get insight into market trends and help you to get a competitive edge over rivals.
Inherently the difference is between a data scientist, who asks the question, and a data analyst, who will seek to answer the questions that the scientist has established. In essence, the two fields are different sides of the same coin and work well in conjunction with each other.
The foundations are laid by data scientists who create easy observations that allow for forecasting future trends, and any insights that might be important for future considerations. However, once the questions have been asked by the data scientist, a data analyst can turn what you don’t know into actionable insights with practical applications.
So when considering the two disciplines, it’s better to consider how they work together rather than pitting them against one another. Data is always an advantage for any business, but it’s important to make sure that this information is usable and organized in a way that an analyst can look at.
The combination of a data analyst and data scientist will help to provide you with workable information and insights as to where your business should stretch itself in the future.
DashboardFox helps in both data analytics and data science. Here are 4 top ways DashboardFox can help, but there are more.
Access: Self-service access to data. If you have data stored in a database or in a spreadsheet, DashboardFox allows a non-technical user to pull datasets quickly with filters and formulas applied without writing SQL code. It’s a very fast and efficient way to open up secure access to your data to a larger audience.
Visualization: Convert data into meaning information. In many cases a visualization helps to spot the trend. DashboardFox allows you to quickly convert raw data sets into visualizations and add them to interactive dashboards where you can overlay filters to explore how the results change based on those parameters. Plus each individual user has the ability to set and save their own filters so they can focus on what is important to them.
Communication: Sharing data via PDF files or Excel spreadsheets has lots of limitations. With DashboardFox you are able to securely give your entire team a web-based dashboard or report of your data. In many cases, you may want to share your data publically on a dashboard or set of reports and with our public view report license, you have the full capability to do that as well.
Budget: Here’s perhaps the best feature, our price. Unlike other BI tools that require a monthly or annual subscription in order to use them, DashboardFox is a one-time fee. Pay once and use forever. And even with a one-time fee, the cost of DashboardFox is less than many tools annually reoccurring price. Put more money toward the focus on your business, and less to your BI solution.
For more information about DashboardFox and how it may help your data initiative, please contact us for a demo and discussion.