Sitecore Solution || Tips & Tricks

Big data is an all-encompassing term for any collection of data sets
so large or complex that it becomes difficult to process them using traditional
data processing applications.
The challenges include analysis, capture, duration, search, sharing,
storage, transfer, visualization, and privacy violations. The trend to larger
data sets is due to the additional information derivable from analysis of a
single large set of related data, as compared to separate smaller sets with the
same total amount of data, allowing correlations to be found to “spot
business trends, prevent diseases, combat crime and so on.
It’s not all about Data but below,

Velocity – It moves extremely fast through various sources
such as online systems, sensors, social media, web click stream capture, and
other channels.
Variety – It’s made of many types of data from many sources
– structured and semi-structured, as well as unstructured (think emails, text
messages, documents and the like).
Volume – It may (but not always) involve terabytes to
petabytes (and beyond) of data.
Complexity – It must be able to traverse multiple data
centers, the cloud and geographical zones.

Now we have understand what is big data,now question arise what sitecore
face challenges without big data capability.

So below are the challenges that sitecore faced prior to 7.5x version.

Performance.
In an online world where nanosecond delays can cost you sales, big data must
move at extremely high velocities no matter how much you scale or what
workloads your database must perform. The data handling hoops of RDBMS and most
NoSQL solutions put a serious drag on performance.

Continuous availability.

Scale:
With big data you want to be able to scale very rapidly and elastically.
Whenever and wherever you want. Across multiple data centers and the cloud if
need be. You can scale up to the heavens or shard till the cows come home with
your father’s relational database systems and never get there. And most NoSQL
solutions like MongoDB or HBase have their own scaling limitations.

Manageability.

Data security.