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Do you know how many e-mails are sent, videos are uploaded onto YouTube and tweets are sent out per day? All types of data is generated and sent around every millisecond and it is very important that we try our best to understand this data.
Many organisations strive to leave a very big digital footprint, but if they do not make sense of the fast paced data that is constantly generating and evolving, they will not benefit from the crucial insights that could be crucial to their success.
Sometimes there is a need to do a big nested if-statement, check the value of one field, and then do something based on that value. For example:
if([Type] = 'Outstanding', [Outstanding Value], if([Type] = Future', [Future Value], if([Type] = 'Current', [Current Value], [Other Value])))
Think of how storing information has evolved over the years: first we had the rolodex (or as some of you might remember- the carousel) and today we have cloud storage, like Dropbox. As the years went by, we continued to improve the way we store important information.
So now what about big corporations and their colossal amounts of data? How has technology evolved so that it stores such private information securely? Well, in 1970, the term data warehousing was coined.
It is the one solution to categorising and storing an abundance of statistics, facts and numbers safely out of reach of those who do not have permission to login.
With the copious amounts of digital data that passes through companies, there's no mystery as to why “Big Data” has been an ongoing business buzzword. However, all the data in the world may be absolutely useless if it cannot be interpreted for others to understand.
Since the beginning of time, humans have strived to make sense of figures and statistics; the only thing that has changed since then is the quantity and details of the data – but not the principles.
So once you've gathered all your data, you need to slice and dice it to display meaningful insights that can help with decision making and help others make sense of important data.
A well designed data model is a significant factor behind the success of a QlikView project. The architecture and structure of a data model must be well thought through to avoid strings of complicated and unnecessary data presenting itself in the future.
Let's focus on what QlikView professional Steven Dark says about rocky data model foundations and starting a QlikView project the right way:
“What all too often happens is that the data model from the underlying source database is pulled in, with its existing join fields and system field names. A developer will be forced to deal with some immediate issues, such as synthetic keys, but will sometimes (once they have something that ‘kind of works') leave it at that. This can sometimes be okay on small data volumes – but it certainly will not scale and causes much extra effort down the line.”
Your company may spend a lot of money on an efficient analytics tool, but what good is it if there is no one to interpret the data correctly? A great analytics tool does not magically make you an expert decision maker. With the volume of data available, even the best tools will not help the less competent people make the right decisions. Many companies have suffered unfortunate blows due to poor business decisions based on incorrect data interpretations.
Successfully culminating the goals and objectives of an organisation requires a strategic and ongoing cycle of communication between supervisors and employees, which calls for excellent performance management skills. Performance management is the systematic process by which an agency involves individuals and members of a group in improving a company's organisational effectiveness in the accomplishment of agency mission and goals.
Big data is big right now, but why? What can big data really do for your business? Well, to sum it up, Big Data can provide your business with the means to make informed business decisions.
There are four business quarters in a year. In between these quarters, your organisation has the opportunity to review all past data and use it to improve strategies, set new goals and formulate reports. Reviewing data can be time-consuming and stressful, however, it is absolutely crucial for organisations to look at their past data to improve future business.