Are You Planning To Embark On An Advanced Analytics Journey?

Paul Pallath

Welcome to the new world! The manner in which data is generated and captured today has come of age. Traditionally the most common way of generating data from B2C/B2B2C business processes was by having interactions captured as part of transactional systems in a highly structured format. But with the changing technological landscape, much has changed in how data is generated and captured.

What data supports this view?

According to the ESG Digital Archive Market Forecast, the growth in data volumes that is driven by unstructured data amounts to more than 88% compared to structured data. What’s more, Computer World states that unstructured information may account for more than 70% to 80% of all data in organizations.

The change has come because we in the 21st century have redefined the way business is conducted. Significant advancement in Internet technology has forced most businesses to establish a digital online presence to stay relevant. Likewise, every interaction that a customer has in the digital online ecosystem leaves behind a digital footprint containing huge amounts of information.

Social media presences, for individuals and businesses, have increased the speed at which information travels. This has made it possible to share opinions in blogs or multimedia content. The result is the constant generation of large amounts of unstructured data.

All that unstructured data is good news for data scientists

However, this is good news for data scientists.

The previous figures imply that we have now Yottabytes [1024] of data at our disposal for deriving business value – and that amount of data is about to increase.

The Internet of Things, with its emphasis on completely connected systems, has resulted in the availability of high-speed, streaming data. This makes it possible for innovations that use data to build technologies to enable machines talk to one another (and perhaps eventually become intelligent enough to remove humans from the loop)! Taking the trend into consideration, Brontobytes [1027] of data to work with will soon be a reality for data scientists.

So, what is the best way for a business to capture and benefit from this information? Of course, capturing the massive swathes of data available is an important part of the Big Data story. But it’s not the most important part.

The most vital activity is to generate insights that add value to your business. This takes vision, it takes change, it takes…advanced analytics.

For organizations embarking on a journey into advanced analytics, it’s vital to keep in mind these important considerations:

  • How do we measure business value and return on investment?
  • How do we use advanced analytics effectively?
  • Is advanced analytics just another technology project?
  • Is Big Data equal to high quality insight?

In next week’s Predictive blog, I’ll discuss each one of these considerations in more detail.

For expert insight on your own digital transformation, listen to Coffee Talk with Game Changers on The Digital Economy: How Organizations Adapt.


Paul Pallath

About Paul Pallath

Dr Paul Pallath is the Chief Data Scientist & Senior Director with the Advanced Analytics Organisation at SAP. With over 20 years of experience in Machine Learning, Paul has several research publications in the field of Machine Learning & Data Mining in International Journals and conferences and has also invented several patentable ideas.  He has a Master’s Degree in Computer Applications with Gold Medal, and PhD in Machine Learning, both from Indian Institute of Technology, Delhi.