Datameer Strengths, Domain Expertise, and Key Differentiators
Datameer introduced Datameer Cloud, running on Microsoft's Azure HDInsight, and fully managed by Datameer. The new enterprise cloud offering delivers big data analytics-as-a-service, providing customers a one-stop-shop to integrate, prepare, analyze, visualize and operationalize data of any size, type or source.
Datameer Recent Developments
In December 2020, Datameer has released a new data access platform, Datameer Spotlight, designed to change the traditional central data warehouse paradigm. The new platform enables organizations to run analytics at scale in any environment and across data silos.
In October 2019 Datameer introduced Neebo, a new product that enables analytics and data science teams to find, combine, and publish trusted information assets in hybrid landscapes. Neebo's self-service platform enables analytics professionals and data scientists to initiate projects in minutes and promptly answer analytics questions or build new models, thereby enabling greater business agility.
Neebo provides a unified access point for analysts, data scientists, and business stakeholders to more effectively leverage all their data science and analytics assets across the enterprise. Neebo works with information assets of any type (e.g. data, documents, reports, code, dashboards, SaaS applications, and data science models), no matter where they reside: on-premises, in the cloud, in SaaS applications, or in web services.
In September 2019 Datameer introduced the general availability of Datameer X, a new release of the company’s industry-leading data preparation and exploration software built for data scientists and machine learning engineers. Now, organizations can speed up machine learning analytics cycles and create robust data flows that feed more data into machine learning models to increase their accuracy.
Yet machine learning analytic cycles remain hindered as data scientists still spend up to 90 percent of their time exploring and preparing data to feed their AI and machine learning processes. Making matters worse, many of them aren’t using the best data to make their models more effective and accurate. Datameer X solves these two critical aspects of data preparation for machine learning with automated functions that shape data for machine learning and large-scale data exploration that finds the best data for the problem at hand.
In March 2018, Datameer made partnership with IBM to create, manage and deploy business data pipelines for IBM's new data science and machine learning platform, Cloud Private for Data. The partnership is a comprehensive approach to simplifying and streamlining data integration, preparation, shaping, and curation in order to extend data science and machine learning for business teams to make accelerated data-driven decisions.
Datameer Customers in ARTW Customer Database
Leveraging a rigorous data-centric research methodology, APPS RUN THE WORLD asks the simple question: Who’s buying Datameer applications and why? And we provide the answers – supported by decades of research – to our clients around the world. Our Customer database has over 100 data fields that detail company usage of Datameer and other enterprise apps by function, customer size, industry, location, implementation status, partner involvement, Line of Business Key Stakeholders and IT decision makers contact details. List of Verified Datameer Cloud customers.
Datameer Overview
Ownership: - x
Number of Employees: 130
Functional Markets: Analytics and BI,
Key Verticals: Banking and Financial Services, Communication, Healthcare, Media, Retail,
Datameer Key Enterprise and Cloud Applications
Datameer Cloud
Datameer Revenues, $M:
| Type/Year | 2020 | 2021 | YoY Growth, % |
|---|---|---|---|
| Total Revenues, $M | Subscribe | Subscribe | Subscribe |
| Enterprise Applications Revenues, $M | Subscribe | Subscribe | Subscribe |
| Cloud Applications Revenues, $M | Subscribe | Subscribe | Subscribe |
* Enterprise Applications Revenues = License + Support & Maintenance + SaaS
** All revenue figures are estimates based on public records, Cloud and Non-Cloud business models in Apps Run The World's vendor database, and annual survey results including vendor feedback.
Datameer Revenue Breakdown By Type, $M:
| Type | License | Prof. Services | Hardware | Support & Maintenance | SaaS | PaaS | IaaS | Other (Non Enterprise Application Revenues) | Total |
|---|---|---|---|---|---|---|---|---|---|
| % of Total Revenues | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | 100% |
| Revenues, $M | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe | Subscribe |
Datameer Enterprise Applications Revenues By Functional Markets, $M:
Datameer Enterprise Applications Revenues By Verticals, $M:
Datameer Revenues By Region, $M
| Region | % of Total Revenues | 2021 Total Revenues, $M | 2021 Enterprise Applications Revenues, $M | 2021 Cloud Applications Revenues, $M |
|---|---|---|---|---|
| Americas | Subscribe | Subscribe | Subscribe | Subscribe |
| EMEA | Subscribe | Subscribe | Subscribe | Subscribe |
| APAC | Subscribe | Subscribe | Subscribe | Subscribe |
| Total | Subscribe | Subscribe | Subscribe | Subscribe |
Datameer Direct vs Indirect sales
| Region | Direct Sales | Indirect Sales | Total |
|---|---|---|---|
| Type % | Subscribe | Subscribe | Subscribe |
| Revenues, $M | Subscribe | Subscribe | Subscribe |
Datameer Customers - Breakdown by Geo, Size, Vertical and Product
List of Verified Datameer Customers
No. of Datameer Customers: 250
No. of Datameer Enterprise Applications Customers: 250
No. of Datameer Cloud Customers: x
No. of Datameer Cloud Subscribers: x
Customers in a range of markets including financial services, telecommunications, retail and IoT are using Datameer as an integral part of their big data strategy, achieving significant and rapid business results.
Leading brands such as Aetna, American Airlines, Bank of America, British Telecom, Citi, National Instruments, Priceline, Sophos and Telefonica all use Datameer to build trusted big data pipelines to feed business-critical analyses.
Datameer Market Opportunities, M&A and Geo Expansions
In October 2019 Datameer closed a $40 million funding round to further extend its leadership position in the enterprise data preparation and exploration market, serve the ever-growing AI market, and to accelerate the development and market introduction of the disruptive Neebo solution. The round — which will help further build out global sales and engineering capabilities — was led by existing investor ST Telemedia (STT), with participation from long-standing shareholders Redpoint Ventures, Kleiner Perkins, Nextworld Capital, Citi Ventures and Top Tier Capital Partners.
In March 2019, Datameer released the Datameer Enterprise platform, which runs on the Amazon EMR by Amazon Web Services (AWS), is now available on the AWS Marketplace. AWS users can now easily buy and quickly deploy Datameer Enterprise directly from the AWS Marketplace. Kicking off its aggressive expansion into Asia-Pacific, Datameer launched teams in Hong Kong and Singapore to meet growing global demand for its big data analytics technology.
Datameer Risks and Challenges
Migrating its existing customers to the cloud.
Datameer Ecosystem, Partners, Resellers and SI
Mostly direct sales. Datameer has partners with industry-leading technology and services companies to provide customers with the best of breed big data solutions such as Amazon, Tableau, Microsoft, Deloitte, IBM and many others.
Datameer Cloud Infrastructure Insights
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- Datameer Public Cloud and Infrastructure (IaaS)
- Datameer Platform (PaaS)
- Datameer Application Delivery
- Datameer Private Cloud and Data Centers
Research Methodology
Data used in research reports are derived from publicly available documents, continuous surveys of applications vendors, customers, resellers, Independent Software Vendors, systems integrators and other verifiable sources.
Vendor shares and market forecast results are based on a combination of existing databases as well as demand side and supply side research conducted throughout the year with validation from vendors, customers, channel partners and documentations such as earnings releases and 10Q and 10K filings, vertical industry studies, regional and country-level statistics from public and private institutions(i.e. colleges, universities, government agencies and trade associations).
For additional information on our methodologies, here's the link:
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