Big data framework is huge, and the applications greater. Let’s see how businesses can strategize big data to help improve their competitive edge.

2. 3 Strategies for Businesses to Create Value
with Big Data
Big Data is the future for businesses, as it aims to improve
productivity, and reduce the wastes for businesses. It is a known fact
that data as such is necessary for analyzing and strengthening the
base of the company. Big data, which translates to large pool of data
that is gathered, analyzed and used in decision making, has helped
businesses conduct themselves profitably by forecasting the future,
and strategizing their moves. In the age of information overload, data
is being captured from every nook and corner, and it is being churned
using various tools, to create meaning and value out of it. If you, as a
business or an individual, wish to utilize big data to create value, then
you need to understand its potential completely. Big data framework
is huge, and the applications greater. Let’s see how businesses can
strategize big data to help improve their competitive edge.

3. PERFORMANCE MANAGEMENT
Here, you need to understand the data, specifically transactional data,
which is available in your database. You will need to run some queries,
and multidimensional analysis, in order to understand the data that is
available. These queries, and the answers that are obtained thereby,
will help you understand the situation, and help you come up with
ideal decisions to manage the situation. Let’s say you are a retail
business, and you need to identify the customer segments that prove
to be profitable for your business. The answer will help you identify
your short term and long term business decisions. The business
intelligence tools used to run these queries and conduct the related
analysis, come with dashboard capability, which also helps generate
multiple reports. The report developers interact with the data made
available from various departments and segments of the business like
HR, CRM etc. The business intelligence tools have integrated the
different segments of the business to make data availability easy and
convenient.

4. EXPLORING THE DATA
If you are a business planning to market your product/service to the
target audience, how will you identify the target audience? There is data
available, but analyzing that heavy size of data will not be possible by a
single individual or team. This is where big data strategy can help you
improve the marketing ability of your business. Data exploration is an
ideal big data strategy that will help improve your targeting abilities.
This strategy uses a large amount of statistics to explore the data, and
identify answers to the questions, which most marketers tend to ignore.
Predictive modeling analytics help predict user behavior while cluster
analysis help identify the customer segments that have similar attributes.
This strategy also helps identify the cluster or customer group that you
can avoid targeting. Data mining techniques are a part of this strategy
which helps retailers identify buying behavior exhibited by the buyer.
Fast and direct results are obtained as a result of the statistical analysis.
Organizations are looking at more effective and automated techniques
to mine the data, and gather relevant results.

5. SOCIAL ANALYTICS
There is a whole load of non-transactional data available on
the internet, specifically on the social media channels. This
data needs to be analyzed to understand the consumer, and
their habits. The data based on the conversations can be
segregated into three major categories: awareness,
engagement and reach. Mentions of the social content can
be segregated as awareness, while interaction and two-way
communication forms engagement. The extent to which the
content has floated across the social media channels defines
the reach of the content. These social metrics are essential
as they help identify the success of social campaigns. Digital
footprints on the social media can be identified and
measured now, with the relevant tools. This data is huge,
and the relevance and need should be measured before
analyzing it.

6. References
https://www.semaphore-software.com
https://www.semaphore-software.com/blog/big-data-for-businesses/
https://images.google.com/ (pics)

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