Albert Einstein (1879-1955) once said: “We cannot solve a problem with the same kind of thinking that we used when we created it”. This blog deals with problems of today’s grown IT landscapes in any kind of business. The symptoms of this problem are high operating costs, low performance, poor data quality, and alike. All of this ultimately leads to an even bigger problem that states “IT often cannot fulfill the requirements of the business anymore”. This problem gets bigger with the accelerating digitalization of our world, which requires the processing of huge amounts of data in real-time.
HD-business and the fundamental role of data
In this digital age, business models are built upon data. Currency and accuracy of information define success or failure. Think of the very first black and white televisions in the middle of the last century. When compared to today’s state-of-the-art yet affordable devices with high definition pictures, surround sound and interactive second screen features, the first black and white TV becomes exemplary of blur pictures and poor sound quality. Would you want to go back?
Enterprises need to ask themselves what kind of picture they have from customers who buy their products and services. In many traditional companies, it will look like the picture on the left above. Digital champions, however, have a detailed, colorful picture of their business in high resolution. This is what I call “high definition business”.
Challenges in existing system landscapes
There is a lot of evidence on how digitalization has disrupted traditional business models and how it has blown away 70% of the Fortune 1.000 companies in just one decade. Why are so many existing businesses struggling with the transition?
Although it is only one-half of the equation, I will focus on IT aspects and not consider the required organizational changes here. When we examine today’s IT landscapes we will find quite a few commonalities, such as:
Today's dominant system architecture paradigm is client-server with dedicated servers for applications and databases.
Historical limitations in computing power have led to fragmented, complex system landscapes with artificially inflated volumes of duplicate and inconsistent data.
Data is exchanged over point-to-point interfaces or Enterprise Application Integration (EAI) infrastructures mostly in asynchronous batch runs.
Operations and maintenance of these landscapes are extremely expensive, and they are not prepared to support the business in the digital era.
The following picture illustrates how IT landscapes look like today from a high-level technical perspective. The systems in the top row represent applications with their respective servers. "Blue" systems are dedicated reporting systems (read only). The systems in the bottom row represent database servers. I have not included mainframe systems in the picture, which we still find frequently. The arrows in the picture represent the data exchange process between applications.
Serious consequences for the business
The above picture does not depict transformation (data filter, aggregation, compression, etc.) of data when exchanged between applications. Therefore, when we look at the complete database of a business we find:
Dozens, if not hundreds, of copies–many of them are inconsistent
Artificially inflated data volumes leading to all kinds of performance issues and huge hardware requirement
Long process durations and outdated information in reporting systems due to long-running data exchange processes (a.k.a. “nightly batch runs”)
Complex internal contracts among systems on how data are exchanged
All the above consequences prove to be extremely expensive and produce a poor level of data quality, which, by far, is not sufficient to successfully compete with digital businesses.
Corporate data pool with SAP HANA
The solution to these challenges is to centralize the storage of data in a single corporate pool. This pool is not only for reporting purposes like most of the “Big data” solutions in the market. It is a transactional database serving all kinds of use cases at once. We will store data in a disaggregated, atomic form with no redundancies in it, and make it available to all applications at the same time.
If we were to make a list of requirements, our corporate data pool should offer the following real and existing customer requirements:
Current and correct data, no duplicates
Lightning-fast response times (well below one second)
Capable of handling the expected data growth
Existing applications continue to run with corporate data pool
Flexible to many requirements from existing and future business processes (transactions and analytics)
Much more cost-effective (as we are shutting down many silos, the cost of operations should drop by at least 25%)
Secure and protectable (not everyone is allowed to see everything)
Enterprise-ready, capable of handling mission-critical applications, scalable
Transition without interruption of productive use of current systems
As a consequence of the above, we would further expect the following:
Elimination of all interfaces between data silos and all related data provisioning processes (ETL, batch jobs, nightly data loads, etc.)
Smaller data footprint (as we eliminate all duplicates)
Lesser hardware (as we are shutting down silos and we expect smaller data footprint)
More efficient development, as we do not need to worry about performance and origin of data anymore
A consistent backup and restore should be very easy to do
The good news is that all this can be implemented with SAP HANA–at least to a certain amount of data volume, which should be enough to serve the majority of medium to large enterprises in the world even with the current technical restrictions.
Non-SAP applications on HANA
SAP customers often misconceive that HANA would run only with SAP applications. For example, if they want to run something non-SAP (such as Java) on HANA, they think they will have to start from the scratch. We have shown in many projects that non-SAP applications continue to run on HANA just like on any other database. The positive out-of-the-box effects are significant, as below:
Up to 500x shorter response times
70% smaller data footprint
Much more capacity at same performance level
Massive parallel query processing at high-performance level
Almost no optimization efforts
Much more flexible data modeling, allows different applications to work with the same data in parallel
Using SAP HANA instead of the traditional relational database offers completely new options to businesses on how to handle their data and how to implement innovative applications. In many cases, the transition project can be fully funded from immediate savings.
You should start your journey today
With new possibilities that SAP HANA offers to businesses and IT out-of-the-box, every additional dollar spent for the old system architecture might potentially be a lost one. SAP HANA is about to change the game in the SAP and non-SAP world. I would advice you begin to explore the journey immediately and develop an individual roadmap. It will save you a lot of money.
(About the author:Detlev Sandel is the director of innovation mangagement at Capgemini. This post orignially appeared on his Capgemini blog, which can be viewed here)
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