MICROSOFT Azure Machine Learning Studio in Predictive Analytics Software

MICROSOFT Azure Machine Learning Studio
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Washington, USA
1975
More than $100 BN
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MICROSOFT Azure Machine Learning Studio USP

Extensive set of cloud services that enables associations to address business problems, construct, oversee, and convey applications on a massive, worldwide system utilizing various tools and frameworks. Microsoft Azure ML Studio can be used to prepare and manage the data they need for machine learning. It can improve productivity through its powerful capabilities that can integrate the current model cycle with that of the app lifecycle. Request MICROSOFT Azure Machine Learning Studio Pricing to get more information.

Summary

Azure ML is an easy to build and deploy Microsoft Cloud solution for predictive analytics. It is a fully-managed solution which is accessible to users worldwide. This solution by Microsoft helps in analyzing large data sets and perform sophisticated calculations. Microsoft has combined capabilities of both, Azure ML and Cortana Intelligence Suite, which has resulted in empowering the entire predictive analytics solution.

Microsoft Azure ML Studio can be used to prepare and manage the data they need for machine learning. It can improve productivity through its powerful capabilities that can integrate the current model cycle with that of the app lifecycle.

Features:
  • Easy to deploy on cloud as well as on edge
  • Removes unnecessary data from sheets that is not required
  • Can perform mathematical operations on input data
  • Cluster can scale automatically to manage loads

Top Usecases

  1. Customer Response Modelling
  2. Risk Management
  3. Financial Management
  4. Fraud Detection & Prevention

360 Quadrants

Strengths and Weaknesses
  • +12 Real Time Dashboarding
  • +5 Customer Data
  • +9 Data Blending
  • +8 Data Preparation (Data Management)
  • +12 Demographic
  • +11 Geo Spatial
  • +7 Marketing Data
  • +14 Report Automation
  • +13 Report Generation
  • +6 Transaction Data
  • +7 Cloud Hosted Data
  • +5 Data Investigation
  • +10 Hadoop
  • +5 Shared Data Sources
  • +6 Statistical Modelling
  • +7 Times Series Exploration
  • +8 Application Developers
  • +6 Business Analysts
  • +9 Consultants
  • +9 Custom Predictive Algorithms
  • -5 Repurposing Data Is Not Easy
  • -14 Visualization Is Difficult
  • -13 Firmographic
  • -11 Interactive Visualisation
  • -14 Location [Pincodes]
  • -10 Static Visualisation
  • -6 Custom Scripting Language
  • -14 Support for Custom Data Connectors
  • -14 Advanced Condition Prediction
  • -11 Apache Spark
  • -8 Auto-scaling
  • -13 Event Detection
  • -13 Hive
  • -12 Kafka
  • -6 Licensing - Data Volume
  • -11 Licensing - Hybrid
  • -7 Licensing - No of Records
  • -9 Licensing - Per data connection
  • -8 Licensing - Per Processor
  • -5 Licensing - Per seat
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MICROSOFT Azure Machine Learning Studio presence in Predictive Analytics Software

Microsoft has maintained its position as a global vendor in offering a diverse set of software and licensing solutions across numerous industrial verticals. Customer satisfaction has always been its top priority, and it thus focuses on the development of technologies which assist users with progress, in-line with the evolving market trends. To serve the demands of its extensive client base, the company spent a substantial USD 11.38 billion on R&D in 2016. Microsoft has been expansively working towards the advancements of predictive analytics tools by following a mix of both, organic and inorganic strategies. Recently, the company underwent a couple of partnerships and successfully acquired Revolution Analytics as a part of the development of its predictive analytics offerings. Additionally, partnerships are playing a major role in strengthening Microsoft’s position in the predictive analytics market space. Furthermore, these partnerships are expanding abilities of Microsoft’s other products, such as Microsoft Cloud and related services.

MICROSOFT Azure Machine Learning Studio Reviews

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Buyer, Education, SME

2
Feb 27, 2019

“Good Product with Some Bad Tooling Options”

Competent enough software, but not easy to use. I also came across some issues in AI tooling. Though Microsoft seems to be putting in enough work in the platform, I feel that it is overlooking basic deployment and infrastructure issues. I would, however, buy this product for the following features: • Better customer data analysis for relation building • Faster Decision Making • Innovation
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Buyer, Food & Beverages, SME

5
Feb 27, 2019

“Azure’s Big Data and Interactive Dashboards Truly Excel”

Microsoft’s AZURE provides big data and interactive dashboards along with best-in-class visualization and deep dive reports. It is also very efficient allowing us to investigate data much faster compared to our older software, which has enhanced productivity.  The wide range of data options has given us the flexibility to serve our diversified customer base more efficiently. It’s cloud-based environment provides more agility with less time taken for setup and installation.
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James Smith

4
Feb 25, 2019

“Cloud based predictive Analytics”

Microsoft offers a cloud solution for predictive analytics which is known as Microsoft Azure ML. This solution is a combination of Azure ML and Cortana Intelligence Suite capabilities. It is a user-friendly platform as it can connect to number of database and enables users to investigate and visualize data with better understanding, speed, and productivity. It offers Big Data solutions with intuitive reports, compelling visualizations, and interactive dashboards. It enables a user to create, schedule, and orchestrate ETL/ELT (Extract, Load, and Transform) workflows through the hybrid data integration service.
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Top Features

  1. Product Features and Functionality / Core Features
  2. Product Features and Functionality / Enterprise Features
  3. Data Management / Real Time Dashboarding
  4. Deployment Type / Cloud
  5. Add-on Funtionalities / Machine Learning / AI
  6. Data Collections / Transaction Data
  7. Data Collections / Customer Data
  8. Data Management / Data Blending
  9. Data Collections / Demographic
  10. Data Management / Data Preparation (Data Management)
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