Big Data Trends Moving
into the Spotlight in 2015
Hi everyone in this blog I’m explaining about big data.
Big data is being generated by everything around us at all
times. Every digital process and social media exchange produces it. Systems, sensors
and mobile devices transmit it. Big data is arriving from multiple sources at
an alarming velocity, volume and variety. To extract meaningful value from big data,
you need optimal processing power, analytics capabilities and skills.
It is no secret that we are in the data age.
Data comes at us from all directions, in all shapes and sizes. As technology
leaders, we are tasked with answering complex questions like: How will we
process all this information? How can it be more accessible? And how will users
benefit from it?
OF SQL AND RELATIONAL ARCHITECTURES:
markets like the Internet of Things and mobile computing continuing unabated,
enterprise data architectures require structured and semi-structured data to
As the lines between
relational and non-relational database management systems blur, SQL continues
to dominate as a preferred method for managing data for the following reasons:
- Scale and performance - Preconceived
notions that SQL lacks scale and flexibility have been dispelled by
advances in in-memory computing and distributed system architectures. It
is now entirely possible for relational databases to easily scale while
providing the familiarity and stability of SQL. SQL also expresses
incredibly complex queries with just a half dozen variations of the select
- Everyone knows it - Decades of usage has
made SQL a de facto data analysis language. With millions of SQL users and
thousands of SQL tools readily available, making a change to some foreign
query language is an uphill battle. The adoption of a SQL
infrastructure inside a big data architecture can also lead to increased
consumption of Hadoop by opening access to a greater population of users
- Stability - Relational database management
systems support the SQL compatibility, transactional consistency, and
enforced schema required by data-reliant enterprises.