By Charlie Berger, Advanced Analytics-Oracle on Jul 26, 2015
Big Data Analytics with Oracle Advanced Analytics:
Making Big Data and Analytics Simple
Oracle White Paper | July 2014
Executive Summary: Big Data Analytics with Oracle Advanced Analytics
The era of “big data” and the “cloud” are driving companies to change. Just to keep pace, they must learn new skills and implement new practices that leverage those new data sources and technologies. Increasing customer expectations from sharing their digital exhaust with corporations in exchange for improved customer interactions and greater perceived value are pushing companies forward. Big data and analytics offer the promise to satisfy these new requirements. Cloud, competition, big data analytics and next-generation “predictive” applications are driving companies towards achieving new goals of delivering improved “actionable insights” and better outcomes. Traditional BI & Analytics approaches don’t deliver these detailed predictive insights and simply can’t satisfy the emerging customer expectations in this new world order created by big data and the cloud.
Unfortunately, with big data, as the data grows and expands in the three V’s; velocity, volume and variety (data types), new problems emerge. Data volumes grow and data becomes unmanageable and immovable. Scalability, security, and information latency become new issues. Dealing with unstructured data, sensor data and spatial data all introduce new data type complexities.
Traditional advanced analytics has several information technology inherent weak points: data extracts and data movement, data duplication resulting in no single-source of truth, data security exposures, separate and many times, depending on the skills of the data analysts/scientists involved, multiple analytical tools (commercial and open source) and languages (SAS, R, SQL, Python, SPSS, etc.). Problems become particularly egregious during a deployment phase when the worlds of data analysis and information management collide.
Not with Oracle. Oracle delivers a big data and analytics platform that eliminates the traditional extract, move, load, analyze, export, move load paradigm. With Oracle Database 12c and the Oracle Advanced Analytics Option, big data management and big data analytics are designed into the data management platform from the beginning. Oracle’s multiple decades of R&D investment in developing the industry’s leading data management platform, Oracle SQL, Big Data SQL, Oracle Exadata, Oracle Big Data Appliance and integration with open source R are seamlessly combined and integrated into a single platform—the Oracle Database.
Oracle’s vision is a big data and analytic platform for the era of big data and cloud to:
- Make big
data and analytics simple (for any data size, on any computer
infrastructure and any variety of data, in any combination) and
- Make big data and analytics deployment simple (as a service, as a platform, as an application)
Oracle Advanced Analytics offers a wide library of powerful in-database algorithms and integration with open source R that together can solve a wide variety of business problems and can be accessed via SQL, R or GUI. Oracle Advanced Analytics, an option to the Oracle Database Enterprise Edition 12c, extends the database into an enterprise-wide analytical platform for data-driven problems such as churn prediction, customer segmentation, fraud and anomaly detection, identifying cross-sell and up-sell opportunities, market basket analysis, and text mining and sentiment analysis. Oracle Advanced Analytics empowers data analyst, data scientists and business analysts to more extract knowledge, discover new insights and make informed predictions—working directly with large data volumes in the Oracle Database.
Data analysts/scientists have choice and flexibility in how they interact with Oracle Advanced Analytics. Oracle Data Miner is an Oracle SQL Developer extension designed for data analysts that provides an easy to use “drag and drop” workflow GUI to the Oracle Advanced Analytics SQL data mining functions (Oracle Data Mining). Oracle SQL Developer is a free integrated development environment that simplifies the development and management of Oracle Database in both traditional and Cloud deployments. When Oracle Data Miner users are satisfied with their analytical methodologies, they can share their workflows with other analysts and/or generate SQL scripts to hand to their DBAs to accelerate model deployment. Oracle Data Miner also provides a PL/SQL API for workflow scheduling and automation.
R programmers and data scientists can use the familiar open source R statistical programming language console, RStudio or any IDE to work directly with data inside the database and leverage Oracle Advanced Analytics’ R integration with the database (Oracle R Enterprise). Oracle Advanced Analytics’ Oracle R Enterprise provides transparent SQL to R translation to equivalent SQL and Oracle Data Mining functions for in-database performance, parallelism, and scalability—this making R ready for the enterprise.
Application developers, using the ODM SQL data mining functions and ORE R integration can build completely automated predictive analytic solutions that leverage the strengths of the database and the flexibly of R to integrate Oracle Advanced Analytics analytical solutions into BI dashboards and enterprise applications.
By integrating big data management and big data analytics into the same powerful Oracle Database 12c data management platform, Oracle eliminates data movement, reduces total cost of ownership and delivers the fastest way to deliver enterprise-wide predictive analytics solutions and applications.