Big data is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytic capabilities and skills.
What is changing in the realm of big data?
Big data is changing the way people within organizations work together. It is creating a culture in which business and IT leaders must join forces to realize value from all data. Insights from big data can enable all employees to make better decisions—deepening customer engagement, optimizing operations, preventing threats and fraud, and capitalizing on new sources of revenue. But escalating demand for insights requires a fundamentally new approach to architecture, tools and practices.
The Foundation for Data Innovation
Enterprise Big Data
We live in a world increasingly driven by data. How your organization defines its data strategy and approach—including its choice of big data and cloud technologies—will make a critical difference in your ability to compete in the future.
- Leverage the benefits of big data in the cloud
- Choose the leading provider to both Fortune 500 firms and top cloud app vendors
- Extend scalability, reliability, and resiliency across the entire environment
- Build on Oracle Engineered Systems for the best price for performance
- Protect investments and skills in the era of big data and cloud
Big data can be characterized by 3Vs: the extreme volume of data, the wide variety of types of data and the velocity at which the data must be must processed. Although big data doesn't refer to any specific quantity, the term is often used when speaking about petabytesand exabytes of data, much of which cannot be integrated easily.
Because big data takes too much time and costs too much money to load into a traditional relational database for analysis, new approaches to storing and analyzing data have emerged that rely less on data schema and data quality. Instead, raw data with extended metadata is aggregated in a data lake and machine learning and artificial intelligence (AI) programs use complex algorithms to look for repeatable patterns.
Big data analytics is often associated with cloud computing because the analysis of large data sets in real-time requires a platform like Hadoop to store large data sets across a distributed cluster and MapReduce to coordinate, combine and process data from multiple sources.
Comments
Post a Comment