What is Oracle Data Miner?
Oracle Data Miner enables data scientists, "citizen data scientists," and both business and data analysts to engage with data directly within the database using a user-friendly graphical interface that features a "drag and drop" workflow editor. As an enhancement to Oracle SQL Developer, Oracle Data Miner (ODMr) adeptly captures and visually presents the analytical steps that users undertake while exploring data and developing machine learning models. The workflows established using ODMr are crucial for not only reapplying analytical techniques but also for fostering knowledge exchange among team members. Additionally, ODMr generates SQL and PL/SQL scripts seamlessly and offers a workflow API that aids in the efficient deployment of models throughout the organization. This capability significantly reduces data movement, ensures scalability for large datasets, upholds security, and accelerates the transition from model creation to implementation. By adopting this advanced methodology, organizations can better leverage their data resources, ultimately resulting in smarter decision-making and enhanced business performance. Furthermore, this systematic approach helps to create a culture of data-driven insights that can transform strategic initiatives.
Integrations
No integrations listed.
Similar Software to Oracle Data Miner
Bright Data stands at the forefront of data acquisition, empowering companies to collect essential structured and unstructured data from countless websites through innovative technology. Our advanced proxy networks facilitate access to complex target sites by allowing for accurate geo-targeting. Additionally, our suite of tools is designed to circumvent challenging target sites, execute SERP-specific data gathering activities, and enhance proxy performance management and optimization. This comprehensive approach ensures that businesses can effectively harness the power of data for their strategic needs.
Learn more
DbVisualizer is a universal database management solution that helps organizations of all sizes work efficiently with relational and NoSQL databases. Built for developers, DBAs, analysts, and data engineers, it scales from startups to teams managing complex environments.
The platform combines a SQL editor with autocomplete, visual query builders, and execution tools for database development and querying. An AI Assistant resolves errors and explains code, while built-in Git integration supports version control and collaboration.
Teams can customize layouts, key bindings, and UI themes, mark frequent scripts and objects as favorites, and apply configurable security settings to meet compliance requirements.
DbVisualizer connects to major databases including MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, SQLite, Cassandra, and BigQuery, and runs on Windows, macOS, and Linux. With nearly 7 million downloads and Pro users in 150 countries, it's a proven fit for businesses of any size.
Learn more
JMP Statistical Software
JMP is a versatile data analysis application that works seamlessly on both Mac and Windows platforms, offering a blend of advanced statistical features and captivating interactive visualizations.
Its intuitive drag-and-drop interface streamlines the data importation and analysis process, complemented by interconnected graphs, a vast array of sophisticated analytic tools, a built-in scripting language, and multiple sharing functionalities, all designed to enhance users' ability to examine their datasets both efficiently and effectively.
Originally developed in the 1980s to capitalize on the advantages of graphical user interfaces in personal computing, JMP has continually progressed by integrating cutting-edge statistical methodologies and tailored analysis techniques from various sectors with each new iteration. Additionally, John Sall, the organization's founder, plays an active role as the Chief Architect, ensuring that the software evolves to meet the dynamic needs of analytical technology. This commitment to innovation and user experience underscores JMP's reputation as a leading choice for data analysis across numerous fields.
Learn more
Oracle Machine Learning
Machine learning uncovers hidden patterns and important insights within company data, ultimately providing substantial benefits to organizations. Oracle Machine Learning simplifies the creation and implementation of machine learning models for data scientists by reducing data movement, integrating AutoML capabilities, and making deployment more straightforward. This improvement enhances the productivity of both data scientists and developers while also shortening the learning curve, thanks to the intuitive Apache Zeppelin notebook technology built on open source principles. These notebooks support various programming languages such as SQL, PL/SQL, Python, and markdown tailored for Oracle Autonomous Database, allowing users to work with their preferred programming languages while developing models. In addition, a no-code interface that utilizes AutoML on the Autonomous Database makes it easier for both data scientists and non-experts to take advantage of powerful in-database algorithms for tasks such as classification and regression analysis. Moreover, data scientists enjoy a hassle-free model deployment experience through the integrated Oracle Machine Learning AutoML User Interface, facilitating a seamless transition from model development to practical application. This comprehensive strategy not only enhances operational efficiency but also makes machine learning accessible to a wider range of users within the organization, fostering a culture of data-driven decision-making. By leveraging these tools, businesses can maximize their data assets and drive innovation.
Learn more
Screenshots and Video
Company Facts
Company Name:
Oracle
Date Founded:
1977
Company Location:
United States
Company Website:
www.oracle.com/database/technologies/datawarehouse-bigdata/dataminer.html
Product Details
Deployment
SaaS
Training Options
Documentation Hub
Video Library
Support
Standard Support
Web-Based Support
Product Details
Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English
Oracle Data Miner Categories and Features
Data Mining Software
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining