Databig Data and Future of Data-Driven Innovation

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DataBig Data and Future of Data-Driven Innovation
A. A. C. Sandaruwan
Faculty of Information Technology
University of Moratuwa
chanakasan@gmail.com
The section 2 of this paper discuss about real world
examples of big data application areas. The section 3
introduces the conceptual aspects of Big Data. The
section 4 discuss about future and innovations through
big data.

Abstract: The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ Heterogeneity, scale, timeliness, complexity, and privacy problems with Big Data impede progress at all phases of the pipeline that can create value from data. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search: transforming such content into a structured format for later analysis is a major challenge. The value of data explodes when it can be linked with other data, thus data integration is a major creator of value.

2. Big Data in the Real World
Big Data talks about this increasing amounts of data
available for companies that can be used to capture
value. In simplest terms, the phrase refers to the tools,
processes and procedures allowing an organization to
create, manipulate, and manage very large amounts of
data. It does not define how much is big; it depends on
the context, as what one company considers big could be
relatively small for another company. So this refers to
data that is large enough that our traditional tools will
struggle to handle not whether it’s terabytes or petabytes of data.

Since most data is directly generated in digital format today, we have the opportunity and the challenge both to influence the creation to facilitate later linkage and to automatically link previously created data. Data analysis, organization, retrieval, and modeling are other foundational challenges. Data analysis is a clear bottleneck in many applications, both due to lack of scalability of the underlying algorithms and due to the complexity of the data that needs to be analyzed.

A major investment in Big Data, properly directed, can result not only in major scientific advances, but also lay the foundation for the next generation of advances in science, medicine, and business.

2.1. Opportunities

1. Introduction

Scientific research has been revolutionized by Big Data.
Astronomy is being transformed from one where taking
pictures of the sky was a large part of an astronomer’s
job to one where the pictures are all in a database already
and the astronomer’s task is to find interesting objects
and phenomena in the database [1, 2].

T

he widespread use of the internet has unveiled
endless possibilities for many different aspects of
the society. The increasingly large amounts of data
available through the internet has made it challenging for
companies to meet the ever evolving needs of today's
society. While the availability of large amounts of data
has created limitless opportunities for businesses and IT
companies; their traditional methods of handling data are
insufficient to explore these new possibilities.

Big Data has the potential to revolutionize not just
research, but also education. Imagine a world in which
we have access to a huge database where we collect
every detailed measure of every student's academic
performance. This data could be used to design the most
effective approaches to education, starting from reading,
writing, and math, to advanced, college-level, courses.
We are far from having access to such data, but there are
powerful trends in this direction. In particular, there is a strong trend for massive Web deployment of educational
activities, and this will generate an increasingly large
amount of detailed data about students' performance.

The notion of Big...
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