Software Alternatives, Accelerators & Startups

Datameer VS NumPy

Compare Datameer VS NumPy and see what are their differences

Datameer logo Datameer

An all-in-one data transformation platform for exploring, preparing, visualizing, monitoring, and cataloging Snowflake insights.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Datameer Landing page
    Landing page //
    2023-06-08

Datameer: Data Quality & Data Prep for Snowflake

Discover, explore, clean, transform, automate, and share Snowflake data with Datameer. The platform equips analysts and data engineers with a complete data toolset to efficiently prep their data.

Key Features:

  • Data catalog: Search and filter datasets using metadata for project-specific requirements.
  • Rapid Fire - No Code SQL Query Builder for data mining
  • Visual canvas-like interface: Easily design and maintain projects for seamless workflow.
  • Insights sharing: Share results and exceptions via Email or Slack with scheduled delivery options.
  • Seamless Snowflake integration: Deploy data assets to Snowflake with ease.
  • GIT version control: Automate version control and CI/CD for Snowflake data pipelines.
  • Materialization and dependency management: Ensure reliable data processing.
  • Cost and Usage Monitoring with drill down exploration
  • Data Quality Checks and Monitoring
  • API Framework for External Triggers
  • AI Support for Prep, Discovery, and Documentation
  • Production Job Scheduling Support and Dashboard
  • Automated Bi-Directional Cloud File Integration from and to AWS S3, Azure, and GCP

Benefits of Datameer Cloud:

  • Increased data accuracy and consistency.
  • Reduced data preparation time.
  • Improved data access and sharing.
  • Enhanced data-driven decision making.

Datameer is a Snowflake SELECT partner, recognized for its data preparation expertise. The platform prioritizes data security, with monitoring by Drata to protect your valuable data.

Unlock the power of your Snowflake insights with Datameer today.

  • NumPy Landing page
    Landing page //
    2023-05-13

Datameer features and specs

  • Aggregate Transformations: Yes
  • Auto Documentation: Yes
  • Automated Email Notifications: Yes
  • BI integration: Yes
  • Data Catalog: Yes
  • Data Discovery: Yes
  • Data Preparation: Yes
  • Data Profiling: Yes
  • Data Transformation: Yes
  • Data Validation: Yes
  • Dataset Joins: Yes
  • Dependency Management: Yes
  • Deployment: Yes
  • Deployment History: Yes
  • Exploration: Yes
  • Extract and Split Function: Yes
  • Filter and Replace: Yes
  • Fresh Data: Yes
  • Full Lineage: Yes
  • Google Sheets Integration: Yes
  • Manage Columns Function: Yes
  • Materialization: Yes
  • Metadata Enrichment: Yes
  • Model Deployment: Yes
  • Monitoring: Yes
  • No Code Editor: Yes
  • Orchestration API: Yes
  • Pivot Table: Yes
  • Production Pipelines: Yes
  • Scheduling: Yes
  • Search: Yes
  • Sharing Insights: Yes
  • Slack Integration: Yes
  • Snowflake Catalog: Yes
  • Snowflake Native: Yes
  • SQL Code Editor: Yes
  • Version Control: Yes
  • AI Support for Prep, Discovery, and Documentation : Yes
  • Data Quality Monitoring: Yes
  • Cost and Usage Monitoring: Yes
  • Bi-Directional Cloud File Integration: Yes

NumPy features and specs

No features have been listed yet.

Datameer videos

Datameer: Efficiently Extract Insights from Your Snowflake Data

NumPy videos

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Datameer and NumPy)
Data Dashboard
65 65%
35% 35
Data Science And Machine Learning
Data Transformation
100 100%
0% 0
Data Science Tools
0 0%
100% 100

Questions and Answers

As answered by people managing Datameer and NumPy.

Why should a person choose your product over its competitors?

Datameer's answer

  • Intuitive Visual Interface: Datameer offers a user-friendly visual interface for easy data prep with or without coding.

  • Seamless Snowflake Integration: Datameer integrates seamlessly with Snowflake, keeping all of your data in Snowflake where it should be.

  • Streamlined Data Analytics: With Datameer and Snowflake, you can unlock valuable insights faster and more efficiently, eliminating complex coding and cumbersome data transformations.

What's the story behind your product?

Datameer's answer

The story of Datameer began with a vision to democratize data analytics. The founders recognized the growing need for a platform that could empower organizations to leverage their data effectively, regardless of their technical expertise.

They set out to create a solution that would bridge the gap between data science and business users, enabling anyone to make data-driven decisions.

Over the years, Datameer has evolved into a leading data preparation and analytics platform, trusted by organizations across various industries to transform raw data into valuable insights.

Who are some of the biggest customers of your product?

Datameer's answer

Datameer caters to businesses of all sizes, from small businesses to large enterprises. Some of it's most prominent customers include BT Openreach, Vivint, BMO Financial Group, Akbank, Skylar, and Reliant Funding. These companies use Datameer's data preparation and analytics platform to make better decisions with their data.

Which are the primary technologies used for building your product?

Datameer's answer

Snowflake - The Data Cloud

What makes your product unique?

Datameer's answer

Datameer offers an intuitive and user-friendly data transformation and analytics platform. Unlike other solutions that require extensive SQL knowledge, Datameer allows users to work with complex data easily through a visual interface. Whether you're a data engineer or a business analyst, Datameer empowers you to derive meaningful insights from your data without requiring extensive SQL skills.

How would you describe your primary audience?

Datameer's answer

Datameer caters to a diverse audience consisting of both technical and non-technical users. Data engineers and data analysts benefit from the platform's powerful data processing capabilities and advanced analytics functionalities. At the same time, business users, such as marketing professionals or operations managers, appreciate the simplicity and accessibility of Datameer's interface, allowing them to explore and visualize data without relying on IT or data science teams.

In essence, Datameer's primary audience is anyone who wants to unlock the value of their data quickly and efficiently.

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Datameer and NumPy

Datameer Reviews

We have no reviews of Datameer yet.
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NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Datameer. While we know about 107 links to NumPy, we've tracked only 3 mentions of Datameer. 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.

Datameer mentions (3)

  • Alteryx Freelancers - How Much Are You Taking Home Hourly?
    Hence the popularity of tools like Alteryx... There are newer better tool now like datameer.com easier to use and more modern. Source: over 2 years ago
  • Alteryx - worth the time investment to learn?
    That's right... Just look at datameer.com it's SaaS so much easier to handover... And much cheaper too... Source: about 2 years ago
  • Alteryx - worth the time investment to learn?
    I am biased but check out: datameer.com. Source: about 2 years ago

NumPy mentions (107)

  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 2 months ago
  • JSON in data science projects: tips & tricks
    Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 2 months ago
  • Introducing Flama for Robust Machine Learning APIs
    Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
  • A Comprehensive Guide to NumPy Arrays
    Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
  • Beginning Python: Project Management With PDM
    A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
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What are some alternatives?

When comparing Datameer and NumPy, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

OpenCV - OpenCV is the world's biggest computer vision library