Competitive Analysis: Stratifyd's BI Analytics Competition

 
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At Stratifyd, we believe in our platform and know that unsupervised machine learning and artificial intelligence are the future of Big Data Analytics. We know that our AI powered platform can go toe to toe with almost any other offering on the market. In order to demonstrate that and to confirm what we already know, we decided to create an honest comparison between Stratifyd and our closest competitors. There are a multitude of companies offering Big Data Analytics today, many of them offer a wide variety of services in several different combinations. For us, we wanted to determine the most relevant needs that we serve, understand how our competitors perform in those areas, and reveal how we measure up.

In order to create a measurable comparison, Stratifyd looked at the most common services provided by Big Data companies. If you are not immediately familiar with these services and what they entail, here is a breakdown to help you understand our matrix.

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Collaboration - The ability to share insights with other team members is crucial to creating faster time to action. Collaborative processes are those that allow easy sharing of reports or dashboards within the team or to other relevant decision makers.

Text Analytics - Most data is in the form to text whether it be structured or unstructured. Text analytics refers to analyzing information from text data and understanding the significance within a textual data set.

Machine Learning - Artificial intelligence is pushing new boundaries across data analytics. Machine learning refers to using that artificial intelligence to automatically process and analyze data to determine significant relevance.

Visualization - Data analysis is only as good as how well you can understand it. Visualization allows for easy assessment of the data through charts, graphs, word clouds, and other visual medium within what the industry refers to as a dashboard.

Sentiment Analysis - When analyzing text data, it is important to understand the meaning behind the words. Sentiment analysis gives businesses the opportunity to understand the feeling and intent behind the words and use that knowledge for action.

Data Preparation - Creating a suitable data format to begin analysis can be a laborious process, and can require powerful tools. Data preparation provides the ability to manage and manipulate information within the same analysis platform saves the headache of integrating different tools.

Statistical Computing - Visualizing your data is important on the surface, but doesn't always help you understand the next level deeper: what is significant and what is not. Statistical computing helps analyze hidden patterns and trends that aren't always apparent to the naked eye.