Book Image

SAP Lumira Essentials

Book Image

SAP Lumira Essentials

Overview of this book

Table of Contents (14 chapters)
SAP Lumira Essentials
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Big data analytics


We are living in a century of information technology. There are a lot of electronic devices around us which generate lots of data. For example, you can surf the Internet, visit a couple of news portals, order new Nike Air Max shoes from a web store, write a couple of messages to your friend, and chat on Facebook. Your every action produces data. We can multiply that action by the amount of people who have access to the internet or just use a cell phone, and we get really BIG DATA. Of course, you have a question: how big is it? Now, it starts from terabytes or even petabytes. The volume is not the only issue; moreover, we struggle with the variety of data. As a result, it is not enough to analyze only the structured data. We should dive deep in to unstructured data, such as machine data which are generated by various machines.

Nowadays, we should have a new core competence—dealing with big data—, because these vast data volumes won't be just stored, they need to be analysed and mined for information that management can use in order to make right business decisions. This helps to make the business more competitive and efficient.

Unfortunately, in modern organizations there are still many manual steps needed in order to get data and try to answer your business questions. You need the help of your IT guys, or need to wait until new data is available in your enterprise data warehouse. In addition, you are often working with an inflexible BI tool, which can only refresh a report or export it in to Excel. You definitely need a new approach, which gives you a competitive advantage, dramatically reduces errors, and accelerates business decisions.

So, we can highlight some of the key points for this kind of analytics:

  • Integrating data from heterogeneous systems

  • Giving more access to data

  • Using sophisticated analytics

  • Reducing manual coding

  • Simplifying processes

  • Reducing time to prepare data

  • Focusing on self-service

  • Leveraging powerful computing resources

We could continue this list with many other bullet points.

If you are a fan of traditional BI tools (later in this chapter, we will compare BI and data discovery tools), you may think that it is almost impossible. Yes, you are right, it is impossible. That's why we need to change the rules of the game. As the business world changes, you must change as well.

Maybe you have guessed what this means, but if not, I can help you. In this book, I will focus on a new approach of doing data analytics, which is more flexible and powerful. It is called data discovery. Of course, we need the right way in order to overcome all the challenges of the modern world. That's why we have chosen SAP Lumira—one of the most powerful data discovery tools in the modern market. But before diving deep into this amazing tool, let's consider some of the challenges of data discovery that are in our path, as well as data discovery advantages.