Data Analytics

Data for better decisions

Data exploration is the first step in determining the right Key Performance Indicators and business driving metrics. Use our Insights module or our Excel AddIn or connect ClicData directly to Python and other tools!

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What is Data Analytics?

Data analysis is a crucial process that involves exploring, cleaning, transforming, and modelling data to identify patterns, trends, and relationships between variables. It is widely used in various fields such as finance, marketing, healthcare, operations, engineering, to gain insights into complex systems and make data-driven decisions.

The data analysis process also includes statistical methods, machine learning algorithms, data visualization tools, outlier analysis and pattern detection, used to identify unusual events or behaviors and recurring trends or patterns in data.

Your data is extremely valuable.
We offer the tools to leverage it.

  • Trending

    Data trending refers to the analysis of patterns and trends within a set of data over time. It involves examining data points over a specific period to identify the direction and magnitude of changes in the data.

  • Cause and Effect

    Cause and effect in data analysis refer to the relationship between two variables where changes in one variable (cause) lead to changes in another variable (effect). In data analysis, cause and effect can be explored using statistical techniques such as regression analysis, correlation analysis, and causal inference methods.

  • Pattern Detection

    Pattern detection is the process of identifying recurring trends or patterns in data. It involves using statistical and machine learning algorithms to analyze data and identify patterns that may not be easily observable to the naked eye.

  • Outlier Analysis

    Outlier analysis is the process of identifying and analyzing data points that are significantly different from the majority of the data in a dataset. These data points, known as outliers, may be due to measurement errors, data entry errors, or represent unusual events or behaviors.

  • Sentiment Analysis

    Sentiment analysis and Opinion Mining are used to identify and extract subjective information from text, such as reviews, social media posts, and news articles. It aims to determine whether the sentiment expressed in the text is positive, negative, or neutral.

  • Diagnostic Analytics

    Identify the root cause of a problem or issue. It is used to troubleshoot problems and inform process improvement for example why a particular product is underperforming, determining the cause of customer complaints, or analyzing the root cause of a process bottleneck.

  • Predictive Analytics

    This involves using statistical models and machine learning algorithms to make predictions about future events or behaviors based on historical data. It is used to forecast future outcomes and inform strategic planning.

Good decisions start
with Insights

Our Quick Insights module and our soon to be available Insights is your first stop to get some correlations, handling missing values, formatting, normalizing, and binning data.

But I really like Excel...

We get it. We love Excel too and it is a great tool and that is why we built our ClicData Excel AddIn that lets you connect directly to all your data in ClicData in just a few clicks - directly from Excel.

Connect multiple data sets to different sections or sheets in your Excel and by clicking one button, all data is instantly refreshed.

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Describe Data
With Metadata

The Data Analysis module lets you inspect the structure of your data, a critical step in determining types of data, ranges, sparsity, gaps and null data and more.

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Leverage The Full
Power of Python

Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy or get more advanced and build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making.

Frequently Asked Questions

What types of data sources can I connect to?

Pretty much all data sources you can think of.  Cloud applications, cloud or on-premise databases, local files, FTP servers, or any REST/SOAP APIs.  That should pretty much cover all your organization's data environment. 

Can I do predictive analysis?

You can leverage ClicData to prep your data and push it back to any system you use to run advanced analytics and predictions. 

How easy is it to use ClicData?

Very.  ClicData is a low-code, no-code platform by design. Integrate data with our Smart Connectors in seconds.  Drag'n'drop dimensions in our Quick Insights and immediately visualize the data.  

What kind of support do you offer?

Our support team is entirely made of experienced data analysts who know ClicData in and out. They will have answers for both your business and technical requirements.  Learn more about our support.

You look interested... Let's chat

Book a 30-minute call with one of our product specialists and find out if ClicData is right for you.