SAP Analytics Cloud – First step towards Corporate Intelligence

[Githen_Ronney]

I have been working in Analytics space for the past 13 years and I strongly believe this is the most exciting time for data enthusiasts. We have grown from a data deprived world to a data rich one in a short span of time. Data is the new age oil so efficient data crunching  is more relevant than ever before. In this extremely competent business world proactively envisaging challenges are vital to the success of any organization. In the past Analytics department helped  Organizations to learn from mistakes by providing Reports / Dashboards  but in the new era no Organizations are having the luxury to learn from mistakes. Existence of Anlaytics department can be justified only if it helps Organizations to automate the process of proactively preventing or circumventing an imminent business challenge. At the same time they have to help business to weave new strategies to stay competitive.  These can be achieved in two steps:

1. Analytics department in an Organization should have the aptitude to harness data from multiple datasources or disparate data siloes. In short data collection is the first step of decision making.


2. Machine Learning / AI Algorithms should be applied on these collected data to find patterns, trends and Insights.

Let us see how SAP Analytics Cloud can be useful in this context. I have just scratched the surface by mentioning some of its key features which attracts me.

SAP Analytics Cloud is unique as it can handle simple as well as very complex business requirements. For example it can handle simple requirements such as collecting data from multiple data sources, Cleaning of data, detecting outliers in data and preparing conventional business intelligence reports. At the same time this tool is versatile enough to manage complex requirements of Planning , predictions, Digital Boardroom, Value Driver Tree, Regression algorithms and R integration. These qualities make SAP Analytics Cloud a dearest tool for both reporting consultants and Data Scientists. Also this has a smart engine under the hood which enables smart predict, smart insight and search to insight functionalities. This smart engine is incorporated into SAP Analytics Cloud by encompassing different Machine Learning and AI Algorithms capable of handling respective requirements.

Most importantly SAP Analytics Cloud is evolving quite rapidly and looking at the pace of its evolution, it is almost certain that it is going to be the go-to tool for future packaged Data Science solutions. Its close integration with programming language R is a future oriented move. R integrations helps to enrich visualization of stories and also enables to implement supervised and unsupervised machine learning algorithms. Powerful packages in R language helps to implement Regression, Classification, Clustering and Association without the need to understand the complex mathematics behind each algorithms. This helps an analytics consultant to find patterns, trends and insights in the given data set without having a formal statistics degree.

Analytics or Business Intelligence department in many organizations is at the cusp of transformation or they are at the cross roads between conventional BI and Artificial Narrow Intelligence. SAP Analytics Cloud can act as a first step in their journey towards attaining AI capabilities. Its simple, powerful and ever growing  ML / AI features helps BI departments to generate basic AI for their Organizations. After all, creating an intelligent enterprise is not a sprint; it’s a marathon. Reports which are relevant last year may not be relevant today due to dynamicity of modern business.   Business / Market is changing on a daily basis so are strategies of companies.  In this hyper-connected business world BI team cannot be stay relevant by merely maintaining some old reports but they have to work closely with decision making team to support them with right Intelligence. In this context SAP Analytics Cloud can help BI team to respond quickly to the business team or work along with them in their decision making process.