• Skip to main content
  • Skip to secondary menu
  • Skip to footer

Technologies.org

Technology Trends: Follow the Money

  • Technology Events 2026-2027
  • Sponsored Post
  • Technology Markets
  • About
    • GDPR
  • Contact

The MapR Data Science Team Addresses All Stages of the AI Lifecycle

September 12, 2018 By admin Leave a Comment

MapR® Technologies, Inc., the industry’s leading data platform for AI and Analytics, announced today at Strata Data Conference six new data science service offerings to help customers gain immediate value from Machine Learning (ML) and Artificial Intelligence (AI) and expand their competitive edge over competitors, no matter where the customer is in their data science journey.

Because AI and ML can be complex, organizations don’t always have the capacity to execute on AI and ML ideas. Those that do, may not be able to bring those ideas to production. According to McKinsey Global Institute, early adopters of ML have a 3 to 15% profit advantage across sectors. Many say they achieve revenue increases by using AI in core processes. Some organizations may lack the internal knowledge and expertise, but this should not hold them back entirely.

“The MapR Data Science team has helped dozens of organizations get to the next stage in their AI journey,” said Joe Blue, director data science, MapR Technologies. “We’ve learned that there is no one-size fits all approach that will work for every organization. When we engage with organizations, we learn where they are in their AI maturity level and what their objectives are to come up with a customized plan to get them to the next level.”

Details of New MapR Data Science Lifecycle Offerings:

AI/ML Hack-a-thon. In this offering, the MapR Data Science team works with the organization to identify a business use case and rapidly prototype a solution. This offering is targeted toward AI and ML contemplators, and is meant to be a short, hands-on session that delivers a real ML and AI solution that the organization will continue to improve and maintain over time.
Data Science Refinery Accelerator. MapR’s Data Science Refinery unlocks container and ML technologies and, with this engagement, an expert will guide customers through installation, best practices, and baseline models to ensure maximum production success. For a limited time, a one-week engagement is included when purchasing the MapR Data Platform, a $15k value.
Cybersecurity Advanced Protection. Network security vendors are usually effective at spotting known patterns, but there are often “unknown” gaps that could allow evolving hackers to gain entry or inflict damage. The MapR cybersecurity data science offering orchestrates a real-time pipeline of logs (e.g. application logs, transaction logs, etc.) and trains models based on the unique signature of network sources and traffic. Ultimately, the organization receives a visual, UI-based assessment showing suspicious activity, allowing internal security experts to review and escalate threats in real-time.
ML Deployment. Building ML solutions to solve business problems doesn’t actually address that problem until the model can make real decisions. The issue is that many environments have limitations in using data and scaling decisions. Intended for organizations that are further along in their ML / AI journey, the model deployment offering maximizes a model’s value by uploading the modeling process to the MapR Data Platform. The solution is then poised to take advantage of all the organization’s data, utilize every ML library, and deliver results that will scale and improve with the business.
AI Enablement. With this offering, the data science team combines the MapR ML framework with Streaming events to deploy an AI engine that will begin to find new opportunities for optimization through a continuous learning and feedback loop. The team uses Machine Learning to bring order to the chaotic nature of a system’s behavior (e.g., a person, a car, a pipeline, etc.), then apply reinforcement learning to teach the system to adapt to identify and assess unusual cases to achieve generalization.
ML Model Maintenance. ML models degrade over time. In many cases, the arrival of performance results lags behind the next model deployment. Designed for mature ML processes, this offering enables organizations to monitor their ML workflows for events that might impact their accuracy in lieu of performance data. Having detected those impacts, the business will be able to make more informed decisions, such as when the current model should be replaced.
“Production success with AI and ML depends on deploying and then evaluating models over time,” explained Ted Dunning, chief applications architect, MapR Technologies. “The ML Model Maintenance offering streams diagnostics and makes it easier to offers better model evaluation, and improves the ability to respond, increasing the agility and effectiveness of an organization’s ML and AI deployment.”

Availability

The new MapR data science offerings are immediately available.

Supporting Resources

Blog: Data Science Offerings from MapR Power the AI Journey

Newly released book: AI and Analytics in Production, authored by Ted Dunning, PhD, and Ellen Friedman, PhD

Tweet this: .@MapR introduces 6 new data science offerings at @strataconf #DataScience #AI #ML Read more: https://mapr.com/blog/data-science-offerings-power-the-ai-journey

About MapR

MapR Technologies, provider of the industry’s leading data platform for AI and Analytics, enables enterprises to inject analytics into their business processes to increase revenue, reduce costs, and mitigate risks. MapR addresses the data complexities of high-scale and mission critical distributed processing from the cloud to the edge, IoT analytics, and container persistence. Global 2000 enterprises trust the MapR Data Platform to help them solve their most complex AI and analytics challenges. Amazon, Cisco, Google, Microsoft, SAP and other leading businesses are all part of the MapR ecosystem. For more information, visit mapr.com.

Filed Under: Tech Tagged With: accelerator, mapr

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Footer

Recent Posts

  • The Humanoid Trap: Form Factor as Distraction in Industrial Robotics
  • Hark Raises $700M Series A at $6B: The Vertical Integration Bet on Personal AI
  • Apple Brings Apple Intelligence to Accessibility, Adds Wheelchair Eye Control for Vision Pro
  • RADAR Raises $170M to Bring Real-Time Inventory Intelligence to Physical Retail
  • Anthropic’s Stainless Acquisition Is an Infrastructure Seizure Disguised as a Developer Tools Deal
  • Blackstone and Google Are Building an AI Infrastructure Giant Outside the Traditional Cloud Model
  • Mind Robotics Crosses $1B in Total Funding; Rivian Is the Quiet Disclosure
  • Quantum Motion Raises $160 Million Series C to Scale Silicon-Based Quantum Computing
  • Fazeshift Raises $17 Million Series A to Automate Accounts Receivable With Autonomous AI Agents
  • Instant Power Becomes the Next AI Infrastructure Battleground as Nyobolt Raises $60 Million

Media Partners

  • Market Analysis
  • Cybersecurity Market
  • App Coding
Quantum Computing Stocks Face Violent Selloff the Moment Markets Reopen Tuesday
The $2.6 Trillion Signal: What Gartner’s AI Spending Forecast Actually Tells You
The Productivity Is Already Here. The Bubble Narrative Is Not.
The Collingridge Dilemma
Why Memory Prices Won’t Come Down
The Bill Comes Due
The Software-Defined Camera Won. The Open OS Did Not.
Cars Are Computers Now, and Most Carmakers Aren’t
Gartner: Global IT Spending to Hit $6.31 Trillion in 2026, Driven by AI Infrastructure
The SDK Generator Benchmarks: Infrastructure vs. Convenience
IdentityTheft.org Sells for $30,000 on Sedo
Infosecurity Europe 2026, June 2–4, London
Ocean Launches From Stealth With $28 Million to Reinvent Email Security Using AI Agents
Salt Typhoon, Volt Typhoon, Flax Typhoon: China’s 2024 Campaign Against U.S. Infrastructure
Foreign Criminal Cyberattacks Against the United States: Ransomware, Botnets, and Financial Fraud
Iran’s Cyber Operations: Infrastructure Attacks, Election Interference, and IRGC Proxies
North Korea’s Cyber Program: From Sony to Blockchain Theft
Russia’s State Cyber Operations: From SolarWinds to Logistics Warfare
China’s Cyber Campaigns Against the United States: Two Decades of Documented Operations
How the U.S. Government Attributes Cyberattacks — and Why It Is Harder Than It Looks
DigitalOcean Launches AI-Native Cloud at Deploy 2026
Verdent Updates AI Platform to Function as a Full Engineering Team for Solo Builders
The Side Project App Is Not Dead. The Side Project App Business Is.
The App Monetization Landscape Has Changed and Most Teams Have Not Caught Up
Building Offline-First Mobile Apps Is Harder Than It Looks and Worth It
State Management in React Native Has Too Many Options and One Right Answer
Mobile Accessibility Is the Case Developers Keep Ignoring
Testing Mobile Apps at Scale Without Losing Your Mind
App Store Optimization in 2026 Is a Different Game Than It Was
Cross-Platform vs Native: The Honest Assessment Nobody Gives You

Media Partners

  • Market Research Media
  • Technology Conferences
  • API Coding
Tuesday Open: AI Earnings Engine Holds the Line as Iran Overhang Fades to Noise
China’s U.S. Treasury Holdings: The Great Repositioning (2021–2025)
Infographic: Why the 2025 CIPA Data Proves the APS-C Renaissance is Real
How WiFi Changed Media
Canva Acquires Simtheory and Ortto to Build End-to-End Work Platform
Netflix Price Hikes, The Economics of Dominance in a Saturated Streaming Market
America’s Brands Keep Winning Even as America Itself Slips
Kioxia’s Storage Gambit: Flash Steps Into the AI Memory Hierarchy
Mamdani Strangling New York
The Rise of Faceless Creators: Picsart Launches Persona and Storyline for AI Character-Driven Content
Baird 2026 Global Consumer, Technology & Services Conference, June 2–4, New York
D.A. Davidson Technology Conference, June 11, 2026, Nashville
Bank of America Global Technology Conference, June 4, 2026, San Francisco
William Blair Growth Stock Conference, June 3, 2026, Chicago
TD Cowen Technology, Media & Telecom Conference, May 27, 2026, New York
J.P. Morgan Global Technology, Media and Communications Conference, May 18–20, 2026, Boston
Technology Investor Conference Circuit, May–June 2026
Automate 2026 Sets Its Agenda Around AI’s Role in Industrial Transformation, June 22–25, 2026, McCormick Place in Chicago
IBM Think 2026, May 5–8, Boston, Massachusetts, USA
AI & Creativity Summit New York 2026, May 14, The Lighthouse Brooklyn
Why Private Domain Data Is the Real Key to AI That Actually Works
Orkes Raises $60M to Bring Production-Grade AI Orchestration to Enterprise Developers
Form.io Launches MCP Server and Agentic Coding Toolset for Governed Enterprise AI Development
Appdome Upgrades MobileBOT Defense With Identity-First Mobile API Protection
Five SDK Generators Compared: Speakeasy, Stainless, Fern, APIMatic, and OpenAPI Generator
API Monetization Models That Work and the Ones That Drive Developers Away
gRPC in Production: What the Documentation Doesn't Tell You
Event-Driven Architecture vs Request-Response: Choosing the Right Communication Pattern
The Business Case for Internal APIs That Most Engineering Leaders Ignore
Breaking Changes: How to Avoid Shipping Them and What to Do When You Must

Copyright © 2026 Technologies.org

Media Partners: Market Analysis · Market Research · Referently · Photography