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  1. Stackups
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  4. Data Science Tools
  5. Metaflow vs Xtract.io

Metaflow vs Xtract.io

OverviewComparisonAlternatives

Overview

Metaflow
Metaflow
Stacks16
Followers51
Votes0
GitHub Stars9.6K
Forks930
Xtract.io
Xtract.io
Stacks0
Followers0
Votes0

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Detailed Comparison

Metaflow
Metaflow
Xtract.io
Xtract.io

It is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. It was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

It is a data solution and technology company that brings in NextGen solutions. We are specialized in data aggregation, preparation, and integration services, to deliver relevant data to downstream systems. Even customized solutions are provider to solve unique data/business challenges.

End-to-end ML Platform; Model with your favorite tools; Powered by the AWS cloud; Battle-hardened at Netflix
Data extraction; Data aggregation; POI data; Media monitoring; Sales and Marketing Intelligence; Data quality
Statistics
GitHub Stars
9.6K
GitHub Stars
-
GitHub Forks
930
GitHub Forks
-
Stacks
16
Stacks
0
Followers
51
Followers
0
Votes
0
Votes
0

What are some alternatives to Metaflow, Xtract.io?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Power BI

Power BI

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

Mode

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

NumPy

NumPy

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

AskNed

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

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