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Datameer, a Big Data BI tool, has been widely utilized by various departments within our organization. Non-technical analysts have found …
Overview
What is Datameer?
Datameer helps businesses clean up, combine, and organize data to make sense of it and use it for reports and machine learning.
Recent Reviews
Pricing
Team/Enterprise
Contact for pricing
Cloud
per month Team
Entry-level set up fee?
- No setup fee
For the latest information on pricing, visithttps://www.datameer.com/pricing
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Product Demos
Datameer: Google Sheets Integration
YouTube
A walkthrough of the Datameer interface
YouTube
Datameer ClickStream Analysis Demo 点击流分析演示
YouTube
Datameer Smart Analytics 智能分析演示
YouTube
Low code vs SQL: What transforms data faster?
YouTube
Product Details
- About
- Integrations
- Competitors
- Tech Details
- Downloadables
- FAQs
What is Datameer?
Datameer: Data Prep & Analytics for Snowflake
Datameer is a solution to discover, explore, clean, transform, automate, and share Snowflake data. The platform equips analysts with a complete data toolset to efficiently prep their data.
Key Features:
- Data catalog: Datasets can be filtered and searched using metadata for project-specific requirements.
- SQL or no-code data transformation: SQL SELECT statements or a visual, no-code interface are available for data shaping.
- Visual canvas-like interface: To design and maintain projects for a seamless workflow.
- Insights sharing: Results and exceptions can be shared via Email or Slack with scheduled delivery options.
- Snowflake integration: Data assets can be easily deployed to Snowflake.
- GIT version control: Automated version control and CI/CD for Snowflake data pipelines.
- Materialization and dependency management: To ensuresreliable data processing.
- Monitoring: To track pipeline performance for efficient data operations.
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 valuable data.
Datameer Screenshots
Datameer Videos
Ryan Goodman, VP of Analytics at Reliant Funding, sat down with us and shared his Snowflake + Datameer journey. “It’s cloud-first. Flip a switch, connect to Snowflake, and go!”
Datameer: Extracting Insights from Snowflake Data
Datameer Integrations
Datameer Competitors
Datameer Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
Datameer Downloadables
Frequently Asked Questions
Datameer helps businesses clean up, combine, and organize data to make sense of it and use it for reports and machine learning.
The most common users of Datameer are from Enterprises (1,001+ employees).
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Reviews and Ratings
(18)
Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
- Recommendations
Datameer, a Big Data BI tool, has been widely utilized by various departments within our organization. Non-technical analysts have found it particularly helpful for running high-power analytics on large data sets, simplifying the complexity of SQL or scripting languages used in Apache/Cloudera tools. The user-friendly GUI of Datameer supports nearly 200 built-in functions and allows for the creation of custom functions from imported PMML models.
Additionally, several departments have leveraged Datameer to aggregate vast amounts of data from different sources, enabling the generation of reports and dashboards for various business units. This tool has also proven effective in building use-case-driven data pipelines, eliminating the need for a dedicated data ops team and resulting in valuable time and cost savings. Its ease of use, without the requirement of coding knowledge, has made it accessible to business teams across the organization.
Furthermore, Datameer has served as a proof of concept for Hadoop for information technology and engineering teams, aiming to provide an analytical platform for all departments. It is the go-to platform for building data pipelines for real-world applications, especially when dealing with unstructured or semi-structured data. For example, it has been successfully utilized to extract, transform, and load data from local servers to a cloud-based data warehouse, supporting the reporting and dashboard infrastructure of the company.
The fact that Datameer users do not need coding knowledge has contributed significantly to its adoption by businesses looking to empower non-technical analysts while still harnessing the power of big data. With its wide range of functionalities and its ability to simplify complex tasks, Datameer has become an invaluable asset in our organization's big data analytics workflow.
Users recommend integrating Datameer with modern data warehouses like Snowflake or AWS and drawing their own conclusions. They find it easy to integrate with Snowflake and perform transformations. They also suggest trying out the tool alongside these data warehouses to see its capabilities firsthand.
Users recommend considering Datameer as an affordable option compared to other vendors like Informatica and Fivetran. They mention that the Spectrum engine autoscale is included in the price, making it a cost-effective choice.
Users recommend embracing Datameer's ELT (Extract, Load, Transform) approach for data processing and seeking support if needed. They appreciate the responsiveness of Datameer's support team.
Overall, users recommend using Datameer for reporting and analytics, especially for working with Big Data. They even suggest using it as a powerful alternative to Excel.
Additionally, users suggest keeping Datameer up to date with the most recent distribution of Hadoop and praising the good support team.
Attribute Ratings
Reviews
(1-1 of 1)Companies can't remove reviews or game the system. Here's why
October 17, 2015
Datameer is great for sum
Score 8 out of 10
Vetted Review
Verified User
Several departments are using Datameer to aggregate large amounts of data from disparate sources.
- Datameer is an excellent "bridge" to Hadoop. Organizations who want to get started with a Hadoop cluster and the analytic capabilities provided by Hadoop, but do not have a large software development team to assist in creating Map/Reduce code are likely to be able to do some very cool things with their data with Datameer.
- The support team at Datameer has been very responsive and quite helpful. Online ticket/email for creation of support tickets, phone or web-ex as necessary.
- Much of the tool will be familiar looking to Excel users.
- Provides a single interface to many of the things a developer/analyst would need to do.
- No specific examples of this in general, but as you mature in your use of Datameer, you may have to decide between investing in training of your staff to use other tools in the Hadoop ecosystem, or you may need to increase your hardware investment a little faster than you would expect to keep pace with demand for the tool as it gains users. One con, specific to our organization is the ingestion-based license model, which could be too expensive for our uses. With other tools such as Hive, HBase, CouchDB, the costs are based on your hardware investment and support contracts (and license fees for Couch).
- It would be nice to have a mature API (web service based perhaps) for sharing infographics generated in Datameer and forward through a proxy or web portal. If we could have used Datameer to provide customer facing graphical output through our other web portals in a secure and manageable way, the value proposition of the Datameer product would have been increased tremendously as a solution. When we assessed doing this more than a year ago, we found the older style security API inadequate for this purpose. I was able to do a prototype use case through custom configuration and development methods around reverse proxies and the custom wrappers I built, but maintenance and administration would have been awkward. At current state of maturity in Hadoop tools, I think using Hadoop and associated tools as a work horse and data lake, as part of a data stream that is secured deep in your environment is the best approach. Reporting tools are maturing quickly to provide connectors to Hadoop, while facilitating report sharing in a proven manner, so I am very, very bullish on Hadoop in the long run. Learn more about Hadoop at www.datafoam.com.
- Cannot determine this accurately due to multiple variables changing simultaneously.
- Hive, Talend Open Studio and Pig
Datameer was not chosen to exclude other tools. Other tools are still used and gaining traction due to their suitability to a task and due to cost-effectiveness of license models. Every organization needs to determine the best approach to the data flow into and out of Hadoop, with considerations that include ease of use, reducing the time to make use of new data, security and governance. If you are new to Hadoop, consider this: Data warehouse techniques and technologies are very mature compared to Hadoop technology and usage, and Hadoop is positioned to dwarf many data warehouse use cases. As you ponder that last statement, the need for enterprise-wide security and governance policies that include Hadoop should become clearer (We do not need a separate data governance strategy for everything else, and something special for Hadoop).
- Quick prototyping/feasibility checking and data-diving
- Enough similarities to Excel usage, that if one spends time in the system, they will figure out how to use as a beginner
- Some complex analytics projects will require many worksheets in a workbook. Because of this, it is easy to lose track of where you are in your logical flow during development. A naming convention for your worksheets (to indicate raw data, filtered data, joined data, etc) will help a great deal. People with a lot of background in development and analytics should be OK, but some business analysts may have a learning curve to keep the model organized as they do the work.