How Data Visualization makes Company Data Work for You?
Aggregation of raw unstructured data from corporate origins, company’s websites, social media channels, offline data or many other sources owes a potential to add value to organizations data base. Failing to realize that they aren’t conveying crisp information but are just creating ambiguity for companies to gauge which data to be trusted and which shouldn’t. This scenario occurs because companies aren’t able to convey the right information in a typically single glance.
Concealed under a large tabular form, there lies a lot of information which needs to be converted into actionable insights. But deriving that insight is a challenge as companies are unable to connect the dots hiding behind thousands of rows and columns of data in their databases. This was the time when companies have humongous data but aren’t sure how to utilize it as the data has stopped making sense now.
Data visualization holds a capability of guiding most of the organizations that have lost their way under high walls of data. But if the same data is been presented in visual format- the patterns, the charts, the images- all of them emerge out so bluntly that everything else is out of sight. Tables, charts, graphs, scatter plots and other data visuals summarize the information making more sense to the human eyes.
Data visualization — knowing the back story
Starting with the basics here let’s first understand why is data visualization? Basically there are 5 major reasons why companies look for visualization tools or services and enlisted below are some that we would agree upon.
· Unable to extract information from this large data sets
· Unable to compare data and take calculative measures
· Spotting errors is difficult
· Revealing hidden patterns or trends is not possible with large data base
· Unable to recall which data is stored where and nothing is in synchronization
So to resolve this paucity of extracting right information from large sets of data base Data visualization was introduced. In simple terms Data visualization is an art of storytelling where you can clearly make people understand thousands and hundreds of data stored in your databases using simple and comprehensible visual context. This can take different forms including pivot tables, pie charts, line graphs, column charts, images…the list goes on and on.
Putting visualization in business
Collecting data from Retail websites, e-commerce store, CRM applications of a bank, website analytics application of a real estate company or social media analytics of a leading manufacturing chain. Do you think all this is easy? Well even if it is, Are you sure your organization is able to make use of all these data collected efficiently? Indirectly there exists a need of data visualization or we can say the existence of data visualization is felt there when you have necessary data in hand but you aren’t able to make the best use of it.
You have your TV remote in your hand and you increased the volume of the television, so how do you know that it is now increased? Of course there is a small horizontal bar showing the range of you volume in that bar. This is the tiniest example of how we are surrounded by data visualization; however in real time, all businesses from retail, real estate, e-commerce or Banking Finance Security and Insurance need data visualization in real time. As we are living in the digital era of technologies like artificial intelligence, machine learning predictive analytics and IoT which is completely overtaking the traditional way of business communication. With all these technologies we can now communicate, operate and predict daily business and personal online offline activities and decision.
How visualization makes data work for you?
We visualize images and pictures more than the tables, rows and columns and while we are already aware of why data visualization is vital for organization but how it turns out to be a savior in this large sea of data is a knowledge that needs to be shared. With unstructured data in data bases, it is a challenge to associate different data points and then analyze them to generate interpretative information. But data visualization makes it easy to narrow down the agenda of using large data sets by dividing it into three major needs:
· Understanding the reasons to create visuals of such large data sets
· Recognizing the factors deteriorating the quality of data
· Constructing the right visuals to shed a new light on the data areas
These three factors give you a clear picture of how visualizing data sets can give you more constructive approach to know your customers and their needs. Using visualization you get an assurance that you are not relying on any assumptions but a derived visuals obtained from cleansed data. There are two ways in which data visualization works. First, it simply represents what the data wants to show; and secondly it highlights data patterns and relativity.
Why contract to service providers, when you have tools?
Microsoft Word or Excel or PowerPoint applications have the capability to create a Smart Art, Charts, and Graphs, diagrams to represent and animate data visually. But this is practically just the beginning of basic data visualizations how about finding some hidden patterns or insights from the same data sets, for that we need some advanced visualization tools. There are tools like Tableau, Dygraphs, ZingChart, and power BI are some of the tools available online for utilizing humongous data using appealing visuals yet we aren’t sure of getting the right output?
While analyzing these large datasets companies tend to completely forget that these datasets might contain errors and can misguide the whole prospect of utilizing large data sets. Therefore the need of companies who hold an expertise in catering the data cleansing services as well as providing appealing data visuals is basic so that companies can rely on trusted data source and get back whenever there is a doubt.
The quality of data, the context of why visualization is been performed and the insights obtained from it is the aim of using an efficient data visualization services. Ignoring the requirements and risks of datasets can complicate organization’s situation rather than clearing the vision.