Overview: Big Data can be defined as data that will be stored in data stores categorized as "NoSQL" due to their lack of compatibility with the SQL language that is so ubiquitous in the relational database world. Typically, though not always, these solutions will exceed a size threshold that causes the user to willingly "give up" the mature capabilities of a relational database for the ability to cost-effectively store, and lightly access, the volume of data. NoSQL is sometimes referred to as "not only SQL" because of the need for both SQL and NoSQL solutions at almost any company.
Most NoSQL is open source and most of the well over one hundred NoSQL open source projects are not data stores. However, there are a significant numbers, perhaps dozens, of them that are.
NoSQL solutions originated out of a need by data-oriented companies like Google, Facebook, eBay and Yahoo to store the massive amounts of information their systems generate. The fate of these companies lies in creating outstanding personal experiences and they are able to utilize every click and every aspect of a page render in their analysis of customer behavior. Commercial software proved too expensive, papers were published and companies took up development of solutions, which soon spread to the community in the open source software development model.
It is important to select the correct category of NoSQL database management system to store the data. Data will be typically stored only once and according to the most important use case due to the high volume. There are five categories:
Certain aspects of NoSQL are common across all the categories and projects:
As companies increasingly begin to understand that no matter what business they are in, they are in the business of information and they need to develop a competency for Information Development to take control of their data. This includes data that is best suited for NoSQL solutions. Some of the data that exceeds the volume, variety and complexity thresholds that make NoSQL attractive include:
The need to manage Big Data and the benefits of mastering it will trump the inertia currently at work upholding the paradigm of loading all data into a database using ETL and then querying that data. BigData/NoSQL solutions have a chasm to cross, but it will need to happen soon. The investment in BigData by the large IT vendors and the investment community certainly supposes adoption well beyond the initial group of Silicon Valley "new economy" companies like eBay, Amazon, Yahoo and Google - companies who, incidentally, wrote many of the solutions. The Big Data landscape could radically change if the adoption does not continue through to the big insurance companies, car manufacturers, healthcare companies and big retailers.
Why should you attend: Big Data Technology and Use Cases provides an approach for storing, managing and accessing data of very high volumes, variety or complexity. Storing large volumes of data from a large variety of data sources in traditional relational data stores is cost-prohibitive. And regular data modeling approaches and statistical tools cannot handle data structures with such high complexity. This seminar discusses use cases and new types of data management systems based on NoSQL database management systems and MapReduce as the typical programming model and access method.
Areas Covered in the Session:
Who Will Benefit: