In the presentation MR KEEPTRAL SINGH talk about data and
its importance in our life. In the first memory processing applications.
Where the people Also he has discussed about some projects
that his company has done earlier. The main focus of his presentation was about
" Interpreting the Value of Big Data with Innovation & Evidence Based
Decision Making ". That was a outstanding presentation and also vary
informative for us as a IT Faculty Student . It will definitely help us on our
future.
Big data is a term that describes the large volume of data –
both structured and unstructured – that inundates a business on a day-to-day
basis. But it’s not the amount of data that’s important. It’s what
organizations do with the data that matters. Big data can be analyzed for
insights that lead to better decisions and strategic business moves.
Big Data History and Current Considerations
While the
term “big data” is relatively new, the act of gathering and storing large
amounts of information for eventual analysis is ages old. The concept gained
momentum in the early 2000s when industry analyst Doug Laney articulated the
now-mainstream definition of big data as the three Vs:
Volume. Organizations collect data from
a variety of sources, including business transactions, social media and
information from sensor or machine-to-machine data. In the past, storing it
would’ve been a problem – but new technologies (such as Hadoop) have eased the
burden.
Velocity. Data streams in at an
unprecedented speed and must be dealt with in a timely manner. RFID tags,
sensors and smart metering are driving the need to deal with torrents of data
in near-real time.
Variety. Data comes in all types of
formats – from structured, numeric data in traditional databases to
unstructured text documents, email, video, audio, stock ticker data and
financial transactions.
At SAS, we
consider two additional dimensions when it comes to big data:
Variability. In addition to the increasing
velocities and varieties of data, data flows can be highly inconsistent with
periodic peaks. Is something trending in social media? Daily, seasonal and
event-triggered peak data loads can be challenging to manage. Even more so with
unstructured data.
Complexity. Today's data comes from
multiple sources, which makes it difficult to link, match, cleanse and
transform data across systems. However, it’s necessary to connect and correlate
relationships, hierarchies and multiple data linkages or your data can quickly
spiral out of control.
Big data’s
big potential
The amount
of data that’s being created and stored on a global level is almost
inconceivable, and it just keeps growing. That means there’s even more
potential to glean key insights from business information – yet only a small
percentage of data is actually analyzed. What does that mean for businesses?
How can they make better use of the raw information that flows into their
organizations every day?
Why Is Big Data Important?
The
importance of big data doesn’t revolve around how much data you have, but what
you do with it. You can take data from any source and analyze it to find
answers that enable 1) cost reductions, 2) time reductions, 3) new product
development and optimized offerings, and 4) smart decision making. When you
combine big data with high-powered analytics, you can accomplish
business-related tasks such as:
Determining
root causes of failures, issues and defects in near-real time.
Generating
coupons at the point of sale based on the customer’s buying habits.
Recalculating
entire risk portfolios in minutes.
Detecting
fraudulent behavior before it affects your organization.
