Excuse me? Online instead of real time; isn’t that the same? Well, have I got news for you: It is not.
Driven by enterprise needs and technological capabilities, enterprises are massively going online. Why do they, and how accurate is online? Why do I read about going online in the news sites all the time? Let me explain, wearing my analytics glasses.
First, let’s get some things straight: Explaining the difference between real time and online starts with a discussion on latency. Latency is a time interval between the stimulation and response, or from a more general point of view, as a time delay between the cause and the effect of some physical change in the system being observed. Online means that there is some kind of interactivity involved, but doesn’t enforce limits in latency. Real time means that there are limits on latency. Pfff, need to re-read that a few times before it starts clearing for me.
Let me give an example: If you move your computer’s mouse, you expect the pointer to react immediately and precisely follow your actions. That’s real time. Another example is playing on a music keyboard controller and have some synthesizer program generating the sounds. Online, however, is when your actions show some response in some timely manner, but there’s no timely relationship enforced to it. For example, starting a video stream from a (remote controllable) webcam may show you the pictures with less than one second latency, or even up to several minutes, yet be online.
My phrasing “difference” should thus be adjusted—real time and online don’t differ, they relate to each other.
The market out there: context awareness and new business models
According to Gartner’s recent Big Data Trends for Business Intelligence, by 2017 more than 30% of enterprise access to broadly based Big Data will be via intermediary data broker services, serving context to business decisions. These are massive amounts and it proofs that digital business require real-time situation awareness. That covers full insight into the things going on inside and outside the organization. Retailers, for example, need to know in real time how weather patterns impact the buying behavior of their customers. The inventory manager requires real-time information when his supplier is in trouble delivering his goods, so he can immediately adjust and use analytics to find alternatives, re-plan, and re-adjust, for example, his forecast.
The issue that occurs is that more and more the enterprises corporate data is insufficient to get the necessary context awareness required to adequately respond to digital business. Think of it; to compete in digital business, a combination of non-corporate data coming from outside the organization is required all the time. This—often unstructured—data could be about social behavior, environmental influences, and government or market trends, to name a few. Some of it is even from premium data brokers preparing data from specific industries or use cases.
We could say that the ability of enterprises to adopt digital transformation and digital business for a big part is influenced by their capabilities of curating, accessing, and interpreting their data to obtain context awareness.
Context awareness is crucial for any enterprise that wants to compete in digital business. Real-time availability of insights is the logical requirement to do so. We already recognized the need for real-time insights to corporate data, however we also now recognize the need for real-time insights in contextual information:
1. Curating insights
Digital business is about the agility to respond to market, customer and environmental influences and actors immediately when required. Digital business requires enterprises to act and respond almost real time to activities not registered in their corporate data.
2. Accessing data and insights
Digital business is about the agility to recognize and access information outside the enterprise that is necessary for curating insights immediately when it occurs.
3. Interpreting and act upon insights
Digital business is about the ability to interpret insights and act upon them instantly. This is not only about interacting with the insights, but especially about applying the closed loop portfolio of analytics: Insights often generate follow-up actions that affect business planning, finance budget allocation, or require new predictive models to argument on influencing variables of the contextual information.
An interesting side effect of contextual awareness is the new business models that come with it. A new category of business-centric cloud services enters the market space that delivers data to be used as context in business decisions, whether human or automated. These information services (or data/decision brokers) will become an essential part of intelligent business operations and smart business decisions.
The case for online analytics
Online analytics is primarily about cloud-based analytics. If we narrow down to business intelligence (BI), the cloud BI market will be worth $4 billion by 2017 whereas the current full BI market (software and services) is estimated at $86 billion.
But how important is the aspect of “being online” for context awareness? Well, it’s quite important:
- Contextual information is very often residing on websites. Your company’s biggest database isn’t your transaction, CRM, ERP or other internal database. Rather it’s the Web itself and the world of exogenous data now available from syndicated and open data sources.
- Products like SAP Cloud for Analytics connect to various cloud-based solutions like SAP S/4HANA, and others. It is obvious that online analytical tools integrate more easily with other cloud-based applications.
- Reduced or eliminated capital costs. Because BI systems are managed on the cloud service provider’s hosted architecture, a user company has no up-front capital investments or multi-year equipment leases with depreciating value. It also stands to benefit from improved cash flow. The subscription fees charged by cloud vendors are treated as operational expenses and don’t incur additional interest charges, which can lead to better cash management and debt avoidance.
- The simplicity of the online, cloud-based analytical applications is key when it comes to user adoption. If we realize that the people creating insights on contextual awareness are business users, you’d agree with me that simplicity makes the difference when it comes to adopting the applications and leverage there power.
- Streamlined system design and increased elasticity. In the cloud, companies can rely on a provider to architect the BI environment, select the technologies that will power it, assemble systems and manage the hardware and software stacks. That frees them to focus their attention on running BI and analytics applications and interpreting the results.
- Fully-integrated business analytics components into the so called closed-loop portfolio. Analytical environments hosted in the cloud comprise a complete end-to-end architecture. SAP Cloud for Analytics for example, spans the ETL, data management, analytics, planning, predictive and risk spectrums, simplifying and speeding the deployment process for users. Cloud BI systems should be ready to use out of the box, so to speak, and the standard setups can quickly be augmented with templates that vendors have developed over the course of different customer engagements.
The case for real-time and online analytics: context awareness
Man, does digital transformation bring us interesting times! There so many aspects of it, with contextual awareness being just one of them. For me, it’s crystal clear that real-time contextual awareness is key to any enterprise that wants to be competitive in digital business. Given the flavor and behavior of the contextual information, online analytical applications can make a significant difference.
For more insight on the power of real-time analytics, see Companies Learn How To Run Their Businesses “Live”.
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