While big data is altering the data landscape considerably
for organizations, how to extract meaning from data remains as challenging as
it ever was.
Part of this challenge rests in how to develop queries that
can effectively probe big data for ground-breaking answers. However, an equally
looming challenge rests in how to create effective reports that present answers
to business users in formats that they can immediately apply to the business or
manipulate for even greater value.
Developing effective reports is an old battle that has
confronted businesses since the dawn of information, let alone the beginning of
the computer age. Most organizations today (as in the past) find themselves falling
within the “80-20” rule, because they are usually obtaining all of
their information from only 20 percent of the reports they have developed, leaving
the rest of their reports to sit on the shelf.
Big data reporting is no different. Once the analytics have
been run against raw data, there have to be effective reporting mechanisms that
give users actionable information. Within most organizations, two types of reporting
mechanisms are needed: the bottom line reports that inform C-level executives and
high ranking managers about various aspects of company performance, and the
more drill-down reporting that gives line managers and staff both information
and tools that they need to further troubleshoot situations. In both cases,
users of reports want ease of use and minimal learning curves.
This invariably raises the question about whether dashboards
or spreadsheets are better for big data reporting.
This is what we know
Automated dashboards that monitor a system’s performance, or
that even monitor elements like online sales as they occur during an Internet marketing
campaign, can flash a “green,” “yellow” or “red”
light to business and IT users signifying whether the item being measured is
going well, proceeding in a cautionary state, or is in a red “halt”
state. For many upper level executives and managers, this is all they need to
take action. If there is a problem, their next step is likely to call down to
the next level of management to troubleshoot the situation.
If you are a manager or staff member at the middle or lower
levels of the organization, it is most likely you will use spreadsheet reporting
and tools to analyze (or even to re-query) the results you have received from
big data analytics. Spreadsheets are flexible software. They allow you to select
on another data field for a sort, or to program computations or macros. With
these analytics “extenders,” you can continue to exploit the value of
the analytics as you drill deeper with your own questions.
Spreadsheet reporting continues to hold its own in
companies, with most organizations possessing “power users” who know
everything there is to know about spreadsheet data manipulation. This is also a
major reason why big data solution providers have continued to employ the concept
of a Microsoft Excel-style spreadsheet, and have even expanded on the spreadsheets
new spreadsheet tools and capabilities that are capable of working with big
Let’s look at an example of customer data that has been compiled
from records of past buying patterns.
Initially, an end user in marketing might be able to see who
the top thousand most profitable customers are, based on volume. But the ability
to further model big data analytics that are delivered to a spreadsheet might
also enable that same user to sort on product mixes or customer demographic
factors. Based on what this person uncovers, he will also have something of
value to report back to upper management that can potentially improve corporate
Big data solution providers understand this dynamic between
the “need to know” at the top level dashboard level and the need to “drill
down” and manipulate at the spreadsheet level. They also know that organizations
will more aggressively adopt their solutions if the solutions come with tools
that are easy to use and already familiar. Dashboards and spreadsheets meet
these requirements – potentially removing some of the unknown factors companies
face as they get their feet wet with big data.
Big data is transitioning from one of the most hyped and
anticipated tech trends of recent years into one of the biggest challenges that
IT is now trying to wrestle and harness. We examine the
technologies and best practices for taking advantage of big data and provide a
look at organizations that are putting it to good use.