BIG DATA!
Big data is a wide term for data sets so
large or complex that traditional data processing applications
are inadequate. Challenges include analysis, capture, data curation,
search, sharing,
storage, transfer, visualization, and information privacy. The term often refers simply to the use
of predictive analytics or other certain advanced methods to
extract value from raw data, and seldom to a particular size of data set.
Accuracy in big data may lead to more confident decision making. And better
decisions can mean greater operational efficiency, cost reduction and reduced
risk.
Analysis of data sets
can find new correlations, to "spot business trends, prevent diseases,
combat crime and so on. Scientists, business executives, practitioners of
media and advertising and governments alike regularly meet difficulties with large
data sets in areas including Internet search, finance and business informatics. Scientists encounter limitations
in e-Science work,
including meteorology,
genomics, connectomics,
complex physics simulations, and biological and environmental research.
The challenge for large
enterprises is determining who should own big data initiatives that straddle
the entire organization.
Working with big data is
necessarily uncommon; most analysis is of "PC size" data, on a
desktop PC or notebook that can handle the available data set.
Relational database management systems and
desktop statistics and visualization packages often have difficulty handling
big data. The work instead requires "massively parallel software running
on tens, hundreds, or even thousands of servers". What is
considered "big data" varies depending on the capabilities of the
users and their tools, and expanding capabilities make Big Data a moving
target. Thus, what is considered "big" one year becomes ordinary
later. "For some organizations, facing hundreds of gigabytes of data for
the first time may trigger a need to reconsider data management options. For
others, it may take tens or hundreds of terabytes before data size becomes a
significant consideration.
Datasprint wanted to
simplify and breakdown the barrier of entering the BIG data analysis market.
How? Simply by offering a platform that can easily connect to your
data securely either via a direct API connection or by a manual
upload process all in under 3 weeks. In the simplest terms we
take your transnational data, crunch it through the super cloud
platform and display actionable trends that your teams at all levels can
understand via a visualisation dashboard and really intuitive menu and story
board system.
Our platform works on a
two folded approach, firstly your teams can review data in
proven visualisation displays and secondly your team can make
critical business decisions based upon the trends discovered and take critical
action. Upon the FREE trial Datasprint offers
its customers, users on the platform are able to engage and interrogate the
last three years of data up to the current LIVE working week to
identify critical actionable trends.
So what is Datasprint?
DataSprint is a software as a service tool
specialising in retention across ecommerce and the online gambling and gaming verticals.
Our gaming operator clients regularly approach us to help them with their most
important customers, their VIP’s.
Their ‘issues’ around their management of VIP’s range from the promotional:
‘are my VIP promotions driving real value?’ through to the strategic: ‘How do I
define a VIP?’ to the tactical:’ am I spotting VIP’s when they visit my
site?’
If you want to learn more on how Datasprint can help redefine retention for your customers please get in contact.
Simon
Elias is a director of DataSprint a
Software as a Service (SAAS) tool focused on improving Profits,
Customer Conversion and Customer Retention for their
clients.
info@datasprint.uk
Their ‘issues’ around their management of VIP’s range from the promotional: ‘are my VIP promotions driving real value?’ through to the strategic: ‘How do I define a VIP?’ to the tactical:’ am I spotting VIP’s when they visit my site?’