2. What is Big Data?
Industry experts categorize big data as data that has one or more of the following
characteristics:
Velocity – Big data comes in very fast through various sources such as online
systems, sensors, social media, web clickstream capture, and other channels
Variety – Big data is comprised of all types data – structured, semi-structured,
and unstructured data
Volume – Big data may involve terabytes to petabytes (and beyond) of data
Complexity – Big data involves complexity that manifests in geographical and
multi-data center data distribution, cloud interaction, and more
3. What does big data mean to you?
Consulting giant McKinsey & Company found companies that were leaders
in the use of big data use grew anywhere from two to 20 times faster than
their competitors who did not use big data well.
The challenge is that traditional relational databases aren’t designed to
capture and analyze big data.
“A new generation of technologies and architectures, designed to
economically extract value from very large volumes of a wide variety of data,
by enabling high-velocity capture, discovery, and/or analysis.”
4.
5. What is NoSQL?
Not everyone has a solid understanding of exactly what constitutes a NoSQL
database. Some think NoSQL and Hadoop (a batch analytic infrastructure
used to process large volumes of data) are synonymous. Others believe
NoSQL always equates to non-transactional systems.
What is true about all NoSQL databases is that they don’t conform to the
legacy relational database model. This frees NoSQL databases to tackle big
data use case situations, store all types of data (e.g. structured,
unstructured), scale to handle very large applications and data volumes, and
easily distribute data anywhere it is needed.
6. What can NoSQL do for you?
Built to cope with the new data management challenges of modern businesses.
Manage all types of data, in many locations, easily scale, and deliver very fast
performance.
Serve as an online transactional processing database, becomes the primary datastore for
online applications, or the “system of record”
Use data stored in primary source systems for real-time, batch analytics, and enterprise
search operations
Handle big data use cases that involve high amounts of data velocity, variety, volume,
and complexity
Excel at distributed database and multi-data center operations
Offer a flexible and dynamic schema design that can be changed without downtime or
service disruption
Accommodate structured, semi-structured, and non-structured data
Easily operate in the cloud and exploit the benefits of cloud computing