data science

15 Free Libre Must-Have Data Analytics Tools for Data Scientists

Hazem Abbas

Jun 24, 2024 — 12 min read

Welcome to our article about the best open-source self-hosted tools for data scientist and engineers. In this fascinating world of data, having the right tools at your disposal is crucial.

From data cleaning to visualization, these open-source tools can make your life easier and enhance your workflow.

Let's have a look at the top 15 free libre tools you absolutely need to consider as a data scientist.

1. Apache Superset

Apache Superset is an open-source data exploration and visualization platform that enables users to create interactive dashboards without extensive programming knowledge. It supports various data sources, offers a wide range of visualization types, and allows for easy dashboard customization and sharing.

It integrates with numerous databases and data warehouses, and includes a powerful SQL editor. Superset also prioritizes security with features like role-based access control and authentication integration. Its extensibility allows for the addition of custom features, and it benefits from a large, active open-source community.

2. Metabase

Metabase is an open-source business intelligence tool known for its user-friendly interface, robust data visualization capabilities, and interactive dashboard creation. It integrates with various data sources, supports live querying, and offers automated reporting.

Metabase also provides tools for data exploration and discovery, ensures security through role-based access control, and benefits from a large, active open-source community. It can be deployed on-premises or in the cloud, offering flexibility to organizations.

3. walkerOS

walkerOS, an open-source framework by Elbwalker, facilitates event-based data collection and processing, mainly focusing on tracking user interactions on websites and applications. It captures events like clicks, page views, form submissions, and more, all structured and collected in real-time for detailed user behavior tracking. The framework also processes this data and can integrate with various analytics, marketing, and data warehousing tools, supporting multiple destinations including Google Analytics, Segment, and Snowflake.

walkerOS is designed for easy implementation, featuring a straightforward setup and minimal configuration, allowing developers to define tracked events through declarative configurations, which reduces the need for custom coding. It follows a modular architecture, allowing for the enablement or disablement of specific features or integrations based on user requirements, ensuring flexibility and scalability.

Moreover, walkerOS provides real-time tracking capabilities, enabling immediate data capture and processing, providing essential real-time insights for user behavior monitoring and timely decision-making.

4. OpenRefine

OpenRefine is a Java-based tool for managing and understanding data. It allows users to clean, reconcile, and expand data with information from the web.

OpenRefine's Key features include faceting, clustering, reconciliation, infinite undo/redo, privacy, and Wikibase.

It operates in a web browser and ensures data privacy by processing data on the user's own machine.

5. Insights

Insights is a self-hosted tool for visually exploring a PostgreSQL database, emphasizing the generation of graphs to show business performance over time.

It supports PostgreSQL connections, auto-detects database schema, allows connection to multiple databases, and enables schema editing and addition of custom SQL fields.

It also features data exploration, filters, time-based graphs, keyboard navigation, saved views, and pinned fields.

Install

npm install -g insights
insights init
insights start

6. Data Explorer by Keen

The Data Explorer project is, maintained by Keen IO, is an open-source interface for querying and visualizing event data. It is written in TypeScript, styled with Prettier, tested with Jest, and is Commitizen-friendly.

7. Retentioneering

Retentioneering is a Python library designed for analyzing clickstreams, user paths, and event logs, offering deeper insights than traditional funnel analysis. It allows exploration of user behavior, user segmentation, and hypothesis formation about user actions.

Retentioneering uses clickstream data to build behavioral segments, highlighting events and patterns that impact conversion rates, retention, and revenue. It extends the abilities of pandas, NetworkX, and scikit-learn libraries for efficient sequential events data processing.

Retentioneering consists of two major parts: the preprocessing module for clickstream data and the path analysis tools for in-depth customer journey map analysis.

8. FlyFish

FlyFish is a self-hosted free premier data visualization coding platform. We effortlessly craft data models and generate a comprehensive suite of data visualization solutions through intuitive dragging.

9. AKShare

AKShare is a Python library designed to simplify the process of fetching financial data. It requires Python(64 bit) 3.8 or higher.

10. Alluxio

Alluxio, originally known as Tachyon, is a virtual distributed storage system that connects computation applications to various storage systems. Originating from a research project at UC Berkeley, it is now used in many leading companies to manage Petabytes of data, with the largest deployment exceeding 3,000 nodes.

11. OctoSQL

OctoSQL is a powerful command-line interface (CLI) tool that offers a unique capability to query a wide variety of databases and file formats utilizing SQL. This tool provides a unified interface that simplifies data access across different sources. The standout feature of OctoSQL is its ability to perform JOIN operations between different data sources. For instance, it allows you to seamlessly join a JSON file with a PostgreSQL table, solving a common challenge faced by many data professionals.

In addition to its querying capabilities, OctoSQL doubles as an easily extendable, comprehensive dataflow engine. This means that beyond just querying data, OctoSQL provides a platform for orchestrating data pipelines, transforming data, and conducting complex data operations. This dual functionality makes OctoSQL a versatile tool for a variety of data tasks.

Furthermore, OctoSQL also enables you to add a SQL interface to your applications. This capability allows developers to incorporate SQL querying within their applications, making data access and manipulation more convenient and efficient.

This feature is particularly beneficial for applications dealing with large amounts of data across various sources, as it provides a standard, familiar interface for data access.

12. Flyte

Flyte is an open-source self-hosted platform that aids in building highly scalable and reproducible data and machine learning pipelines. Its foundation on Kubernetes allows it to ensure scalability and reproducibility.

User teams can utilize Flyte's Python SDK to create pipelines that can be deployed effortlessly on cloud or on-premises environments, promoting efficient resource use and distributed processing.

The platform offers a robust type engine that supports writing code in Python or any other language. Additionally, Flyte provides the ability to execute models either locally or on remote clusters, delivering a high degree of scalability and ease of deployment.

13. Danfo.js

Danfo.js is a JavaScript package inspired by the Pandas library, designed for easy and intuitive work with relational or labeled data.

It supports TensorFlow.js tensors, handles missing data, allows for size mutability with the insertion/deletion of columns from DataFrame, and provides both automatic and explicit alignment of objects.

Features

Fast and supports Tensorflow.js tensors
Easy handling of missing-data (represented as NaN)
Size mutability: columns can be inserted/deleted from DataFrame
Automatic and explicit alignment
Powerful, flexible group-by functionality
Easy conversion from Arrays, JSONs, List or Objects, Tensors into DataFrame objects
Intelligent label-based slicing, fancy indexing, and querying
Intuitive merging and joining data sets
Robust IO tools for loading data from flat-files (CSV, Json, Excel)
Powerful, flexible and intuitive API for interactive plotting
Timeseries-specific functionality: date range generation and date and time properties
Robust data preprocessing functions like OneHotEncoders, LabelEncoders, StandardScaler and MinMaxScaler

14. Knime

KNIME (Konstanz Information Miner) is an open-source data analytics, reporting, and integration platform that empowers organizations to harness the power of their data. Originating from academic roots, KNIME has grown to become a versatile tool widely adopted in various industries, including pharmaceuticals, finance, and manufacturing. It offers a user-friendly graphical interface, enabling users to design data workflows without extensive programming knowledge.

By simply dragging and dropping nodes, users can connect data sources, perform complex analyses, and visualize results seamlessly. This intuitive approach to data analytics democratizes access to advanced data science techniques, making it accessible to a broader audience.

One of KNIME's standout features is its extensive library of over 2000 nodes, which cover a wide range of functions from data preprocessing and transformation to machine learning and deep learning. These nodes are modular and reusable, allowing users to build sophisticated data pipelines with minimal effort. Additionally, KNIME integrates well with other data science tools and languages such as Python, R, and Java, enhancing its flexibility and capability.

This interoperability is crucial for data scientists who often need to leverage multiple tools to tackle complex problems.

KNIME also supports Big Data environments and can connect to various databases, cloud services, and data warehouses, making it a robust choice for handling large-scale data projects.

15- Elementary

Elementary is the premier, dbt-native data observability solution designed specifically for data and analytics engineers. With a setup time measured in minutes, you'll gain instant visibility, have the power to detect data issues swiftly, send actionable alerts, and comprehensively understand impact and root causes. Elementary proudly presents two offerings: an innovative open-source package and a superior managed platform.