
Secoda
Collibra
Atlan
Trello
Alation
Dawiso
Hygger
Zube
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Secoda unifies your data catalog, governance, and observability tools into one platform, providing the fastest way to explore, understand, and utilize organizational data. With a single source of truth, Secoda empowers data teams across industries to monitor the health of their entire data stack, reduce costs, and enhance efficiency. It integrates with all data sources, ensuring reliable, high-quality data with less effort and greater adoption across both data and business teams.
Why Secoda Stands Out: AI-Driven Automation: Automates data management tasks, reducing manual work and boosting efficiency. Includes AI-powered search and an AI Slackbot to enhance data discovery and communication.
User-Friendly Interface: Intuitive design accessible to users of all technical levels, enabling quick actions based on insights.
Advanced Data Quality Features: Includes column profiling, monitoring, and a Data Quality Score, providing full audits and actionable suggestions for improving data quality.
Extensive Integration Capabilities: Seamlessly integrates with existing tech stacks, making it adaptable for organizations of all sizes.
Secoda
MatplotlibBased on our record, Matplotlib seems to be more popular. It has been mentiond 114 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
Collibra - Collibra automates data management processes by providing business-focused applications where collaboration and ease-of-use come first.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Atlan - Atlan is an advanced data workspace developed to offer benefits to many different sources of data.
NumPy - NumPy is the fundamental package for scientific computing with Python
Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.