machine learning & advanced analytics

Leverage Data Scripts to

Perform advanced data analysis and statistics on all your ClicData datasets using Python.

platform data analytics python

You're gonna ❤️️ Data Scripts...

No Installation. Ready to go!

Data Scripts doesn't require any installation. Log in to ClicData, create a new script - you're ready to go!

Central Place for Analytics & ML

Bring your data in once and for all. ClicData is your data hub for all analytics and machine learning projects.

Machine Learning Models

Implement your machine learning models and algorithms directly on the platform to get more insights from your data.

Custom Transformations

Use Python to apply custom data transformation functions to your data when standard functions are not enough.

Built-in Python script editor

Write custom Python scripts directly in the application using our Data Scripts module.

Use datasets from your ClicData account, add parameters and variables, or output your script results to a new dataset.

Leverage AI to generate code from natural language queries.

data script
platform packages

Quick set up with
pre-installed libraries and packages

Perform advanced statistical analysis, machine learning, and more using libraries like Pandas, NumPy and SciPy.

Hit the ground running with our pre-installed packages or install your own.

Full database performance

Run your Python scripts efficiently within the platform. Take advantage of the optimized database infrastructure, performance, and scalability.

Data Scripts eliminate disk overload issues so you can run other tasks at the same time

Monitor CPU and memory usage percentages to ensure optimal performance and resource management.

platform database
platform schedule

Automated tasks and
data updates

Schedule Python scripts execution at specific intervals.

Reduce the risk of human error and free up resources for high value work.

Feed your models with up-to-date data ensuring accurate and timely insights.

One Python Scripting module, endless possibilities

  • 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 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.

  • Programming

    Use Python to go beyond data analysis and machine learning, and develop new connections via API or scrap online data for brand coverage, crisis management or any other business use case.

FAQ

Resources to get your Machine Learning projects off the ground

blog ml ai deep learning data science guide
BLOG

Understanding AI, Machine Learning, Data Science, and Deep Learning


AI, machine learning, data science, deep learning, we tend to use them interchangeably. While there are overlaps between these fields, they do have their own…

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BLOG

Why Statistics for Machine Learning Matters


All modern predictive models involving machine learning rely on statistical algorithms. Statistical techniques capture patterns within data which form the basis of data modeling and…

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EBOOK

What’s the role of Machine Learning in BI applications?


Machine Learning is an increasingly trending topic. Tech lovers and developers write and talk about it, but…

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