Is Your Organization Ready for Data Analytics?
Jig
November 17, 2016
The Data Science and Analytics field has seen some of the most important technology developments of recent years. Our increasingly-digital lives and rapidly-automating business and industrial practices generate an immense amount of data. Those who can help organizations (and people) make sense of this information are in demand today.
Previously, graduates of Pointwest’s successful Data Science Bootcamp talked about some of the challenges facing the Data Industry here in the Philippines.
Now, the senior members of Pointwest’s Analytics Team will take a closer look at the state of Data in organizations in the country, and provide insights to help you determine if your organization is indeed ready for data analytics.
Data and Analytics: An Overview
In a bootcamp for Data Management, Arnold Candelaria, Program Manager for Data Management and Analytics, taught the participants to look at Data as the representation of facts.
“I tried to describe Data as something that captures a fact. So, we know what fact is, it’s something we encounter on a day-to-day basis. But, when that fact gets captured in an electronic format, it becomes the ‘Data’ that we commonly refer to in the field of Information Technology.”Arnold Candelaria, Program Manager for Data Management and Analytics
But, you may ask: What then is Analytics all about?
In a nutshell, Analytics is the science of obtaining insights from the data that you have. Many have likened analytics to its predecessor, which is business intelligence, and both are similar in terms of generating actionable insights from past data. But, in the case of Analytics, IT Techniques play a significant role. For one, software is used to process large amounts of information that are treated as the object of an Analytics job.
Has it Always Been Like This?
Data and Analytics existed in one form or another before the current era. People have been keeping records of activities (the data part) while using them to make decisions (the analytics part) perhaps as early as when man first started writing.
So what is it with today’s world that bred this new industry that’s shaping the way so many decision makers think and act?
“It’s becoming more important now because of the technologies that are developing, and Data is becoming more available and easier to get,”Evelyn Jacinto, Manager on Data Science.
In the past, using Focus Group Discussions and running Market Surveys were often used to try and understand the target market. These were just but some of the traditional ways of getting information about the preferences and behavior of their existing and potential customers.
Alternatively, Data Science allows people to know more about clients and target audiences simply by looking into the information they leave when they engage their digital channels. Likes and shares, duration on a webpage — all these and more can paint a picture of consumer behavior.
“Today, there is an opportunity to market to a worldwide audience, and you don’t necessarily need to meet them,” Evelyn said. “You can learn more about them through data.”
Knowledge taken from distilling the available information gives organizations that effectively use Data Science an edge over their competition. As Evelyn pointed out, organizations who do not do so might find themselves left behind.
The Need to Organize Data for Analytics
Data Management according to Arnold is all about ensuring that data becomes useable as information. Preparing and organizing data means turning it into an information asset that an organization can derive value from. If data is not managed, it has no value.
“The value that you can get out of data begins to be realized when you think about where to use it; where you can apply insights you can get from that data,” Arnold said.
Arnold adds that managing the whole lifecycle of data is similar to any regular asset of an organization. From as early as planning and the time the data is created, all through to the time you act on the information, the entire process has to be managed and organized to get something of value from it.
Jason dela Pena, Technology Center of Excellence Manager, elaborated more on the quality of one’s data. Since data can be assumed as fact, it can mislead if it is highly inaccurate. Redundant, duplicate, or stale information can be dangerously inaccurate.
Similarly, Evelyn pointed out that data can definitely be in a disorganized state. This comes from getting data out of many different sources. To identify the data that is relevant for analytical purposes, Evelyn says rules are needed to identify the correct ones.
Are You Ready for Data Analytics?
With these in mind, the question of whether or not the enterprises in the Philippines is ready for Data Science becomes relative to the state of their data. You may even ask yourself the same questions:
- Did we plan our data lifecycle from the beginning? Have we started to at least plan moving forward?
- Have we maintained the quality of our data in terms of timeliness and preventing redundancy?
- Is data consistent across all the different data sources that we have?
If you have answered yes to these 3 basic questions, then you are one of the few who may be ready.
Is it too late to organize your data for Analytics?
Definitely not, but as your company grows, your data grows with it. And even before your data grows further, it becomes all the more critical to organize the information for you to utilize Analytics sooner than later.
Remember, younger competition who were established with Data Science in play will be planning their data from the get-go and take advantage of Analytics to understand customers better and faster.
Sooner or later, you may be the one playing catch-up.
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Founded in 2003 by pioneers of the Philippine Global Sourcing industry, Pointwest creates value for its list of satisfied clients — including top Fortune 100 and local companies — with world-class IT and BPM services backed by international-standards methodologies and innovative practices.
