Data Ready for a Data-Driven World
Be the change and tackle a digitally transforming world that runs on numbers and metrics. Stay ahead of your competitors, cater to stakeholder expectations, to become a data driven organization.
Data Analytics and Visualization Process
Data Analysis Tools
Most frequent questions and answers
Are data visualization and information visualization same things?
Both are related but not the same concept. Information visualization is about emphasizing data which is important for your business. In that manner, infographics are good samples of information visualization. On the other hand, data visualization is more likely graphically showing raw data.
What is data analytics and visualization?
Data analytics is the science of examining raw datasets in order to obtain an outcome regarding the information they hold. It allows us to identify patterns in the raw data and extract valuable information from them. These results are more likely to make sense for data visualization tools. So, you can have clear and simple visuals that represent focused information.
Why is data visualization important?
The process of data analysis in large data sets is hard and you cannot expect everyone to understand it as data analysts do. Data visualization is the easiest way of telling analysis results to anyone. You can speed things up in your business by clearly visualizing information.
What is Data Analytics?
Data analytics is the science of examining raw datasets in order to obtain an outcome regarding the information they hold. It allows us to identify patterns in the raw data and extract valuable information from them.
When is the right time to deploy an analytics strategy?
Analytics is not just for once or for any special event, it is a continuous process. Businesses should not take their concentration off analytics and prepare to utilize it as a regular business function. Once businesses begin comprehending the potential analytics to resolve problems, they start using all kinds of strategic and general business decisions.
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