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!

Your data is extremely valuable.
We offer you 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

Tired of spending hours manually checking for trends, anomalies, and errors in your data? With Insights, quickly analyze the content of any dataset visually.

Identify outliers, ensure data sanity, and detect trends with ease so your data is prepped for visualization.

aperçu rapide
excel addin

But I really like Excel...

We get it, we do too!

With ClicData Excel Add-In, quickly access all your data from ClicData, directly in Excel, in just a few clicks.

Connect multiple data sets to different sections or sheets in your Excel.

All you have to do is select a cell and Get Data to start working with your data instantly - yes, all data is automatically refreshed.

Describe Data
With Metadata

Inspect the structure of your data with our Data Analytics module, so you can easily determine data types, ranges, sparsity, gaps null data, and more.

Leverage The Full
Potential of Python

Perform exploratory data analysis and apply analytical techniques to real-world datasets using Pandas, Numpy, and Scipy libraries. Or get more advanced, and build regression models using ML sci-kit-learn library for prediction and decision making.

Frequently Asked Questions

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