FLi: Tech Buzz

Sometimes this is just plain SaaS (software as a service). Similar to an application running off your computer, SaaS is where the application reside in remote servers instead and where you as a user only need to be connected to the server to use it. These can include familiar applications like accounting, feedback service tracker, notes organisation, spreadsheet, word processing, inventory management, CRM, or even full-fledge ERP systems. The list goes on. In a similar fashion as social media like Facebook, we connect to the site, log in with our credentials, and then we use the application to manage our information (basically whatever we see on the screen). And we can again view and manage the same information of ours when we are on another computer, and very often also the same is immediately available on our mobile devices.

PaaS (platform as a service) is another. Instead of owning physical servers, and consequently having to also have to deal with the care of physical space, air-conditioning, networking, rack-space allocation, power supply, UPS, and IT manpower, businesses can subscribe to cloud servers and do away with many of the server associated burdens. Essentially with PaaS, you pay for computing powers, memories, disk storage, often with popular OS and database applications pre-installed, etc, and then fire up and configure the servers remotely.

In many cases today, one can fire up a cloud server with popular OS choices (Windows or various flavours of Linux) in a matter of minutes – although in reality production servers needs more deliberate planning but the good part is that the cloud servers can be made ready very quickly once the configurations are worked out. In comparison, procuring and deploying physical on-premise servers often take weeks to months to realise. And because physical servers are not easy to change, decisions tend to take a lot longer to be finalised, adding to the lead time. With more reliable network connectivity today (>99.9% availability: ref.), cloud option is getting more and more attractive.

There use to be a time when radio was king, then came TV, then came PC. We are talking about the media people spend most time on. Today, mobility is where people spend most time on, overtaking traditional media like newspaper, TV and radio – studies have shown. Well, even without studies, it is quite obvious these days that people are actually spending a lot of time on their mobile devices.

And it is not just about social activities. Lots of work activities are migrating to the mobile platform. People realise that and businesses will continue to find more ways to take advantage of the convenience and ever-presence of our mobile devices.

The implications is that web-sites now increasingly have to be made responsive (the ability of the web-site to adjust display layout according to screen size/viewport – and not, as some may mistaken, the ability to respond to user inputs). Many modern and forward looking web-sites are already responsive and that goes a long way in not cutting out your mobile visitors to your site. Having a dedicated mobile app is another popular strategy. Provided users are willing to download the app, mobile apps tend to have more permanence in the users device as oppose to a mobile-friendly site.

There was a time not too long ago that some computer hardware struggles even to run it's own operating system. Today, computing powers are so much better that you can comfortably host another operating system on top of another operating system – and have both running smoothly.

Virtualisation is the running of virtual computers, often many of them, on top of one computer hardware (although it can often be many hardware pooled together). It breaks away from the traditional notion of one hardware to one computer; the idea of virtualisation actually extends beyond just the CPU, to network connectivity, and random-access-memory, and storage, etc.

The pooling of physical bare-metal hardware resources to multiple server computing needs not only improves energy efficiency and space usage, it also improves the high-availability (H.A.) performance that is vital for most server applications.

It might have started with 3 V's, then 4V's, now 5V's is not an uncommon reference when discussing Big Data. Volume. Velocity. Variety. Veracity. Value.

Why big? The sheer volume of data growth on the internet is, well, big. Your selfies, we-fies, emails, your text messages on various platforms, social media, pdfs, voice, videos, photos, and more photos, the "Likes", the thumbs-ups, etc, etc., are information recorded continually. Information is being generated at a rate of terabytes per day. Terabytes, as in, thousands or Gigabyte (which in turn is a thousand Megabytes). That is volume and that is also variety, and the fast rate data is being generated, that is high velocity.

With so much information generated, including structured transactional and analytical data coming from enterprise systems, there is a need to ascertain correctness: veracity.

And then the most important of the V's, value. Why all these fuzz about Big Data if there is no value? With Big Data, and add to that (if) ability to draw and discover new insights, it is believed that there is a huge opportunity to add new business value from insights and possibly foresights from Big Data.

The Internet of Things (IoT) is about things (embeded with networking electronics) that continue to be connected to the internet for all kinds of sensor data collection. IoT growth is expected to drastically outpace the growth we saw with smartphones in the past decade. The potential impact of this is still pretty much projections at this point. People will surely find creative ways to leverage on this development.

On a personal scale, future smart homes will have all kinds of electronics that are connected so you can remotely check and control home devices. Your car for instance, can have sensors that your service center can monitor continously for you. On an enterprise level, sensors can be place at every potential point of failure and monitored and managed for preventive maintenance reducing actual system downtime. There are potential application in just about anything. Just run "IOT prediction" search on your browser and you'll see that people expect many many billions of devices to be connected, and many trillions of dollars revenue is projected to be come from IoT. It is certainly another "watch-this-space" thing.

Information technology gave us tools to efficiently move and manage data, that when collated appropriately give us information in our data warehouse. One common use of information is to meet enterprise processes needs: the sales-order details need to go to fulfilment department, that in turn may trigger warehouse or procurement, and so on. The other important use is analytics.

In addition to the term analytics, there are common reference to similar and seemingly-related terms like business intelligence, and data science. Are they the same? Related? Complimentary? Or are the different labels merely products of creative marketing zeal. Are these perhaps differentiated by one being provider of insights (past) against one having predictive capability (future), or whether it is really about the difference about laymen usable UI (user interface) against in-depth mathematical modelling, or are the differences about the different focus on running-the-business against growing-the-business?

Nevertheless, the current proliferation of information, Big Data, and with the expected explosive growth of IoT (internet of things), there is already and will be more and more data that businesses can draw insights or predictive capabilities from. Whether you merely want analytics to help with better efficiencies in your operation, or you a looking to insights to drive your strategic business directions, analytics is a potential differentiator between enterprise that continue to function in the dark and those who function with insights, and foresights perhaps even – to their business, to their sector, their brand, their market, or anything that might influence their businesses.

Before the age of social media, businesses have very little knowledge about what their customers are – actually – saying about them. There is really no way for business to know what people discuss with their friends and close associates, where their frank opinion often will be expressed. Now, with social media, where people "talk" with their friends and associates online, businesses actually can "hear" those opinions!

This new ability to actually "hear" – first hand – what your customers are saying allows marketeers a more accurate assessing of customers' sentiments. In fact, it is not uncommon now for staffs to check out various social media sites to see what people are saying about their company, except that they are doing it on an ad-hoc basis and are manually scouring the net.

Social media analytical tools can help scour the social media space automatically, periodically, and therefore more reliably, to identify related mentions of brand/industry/product/etc, and then further interpret the sentiments of such mentions using linguistic processing algorithms. From the unstructured social media, these information are transformed to a more structured domain that in turn are collated for dashboard displays.

Databases, or Relational Database Management Systems (RDBMS) are the basis of many applications today. While this is not new, it is so prevalent in our technology landscape today that it is worth a mention here.

Our business data are related. Our sales data are related to customer, and also related to our product lists, that in turn is related to our procurement data. Our deliverables are related to our orders, that in turn are related to our inventories/resources, and those in turn are related to our supplies. It goes on and on.

In reality, related business information are very complex, connecting often hundreds of tables. And people have figured that the most effective way to keep track of them and to keep their relationships in tack is to use RDBMS. In fact, there are hardly any application today that do not use databases.

A further, and valid, question today is there can be too many separated, disconnected databases that one enterprise may own – perhaps due to how each system was implemented at different times, or that they come from different vendors. But they are all nevertheless data that really ought to be integrated into one enterprise database, since they do belong to one enterprise. In reality, full integration can be too complex and time consuming, particularly for SMEs, and it may be more practical to configure sharing of data arrangements between enterprise-owned systems instead.

IT infrastructure, well, is again not a new thing actually. But like the roads, power plants, the ports, the ISPs, and transport systems that a country function upon as their effective infrastructure, the IT infrastructure is similarly vital to the enterprise of today. At every point where you want to electronically connect to your integrated system, you need your network connectivity. Your wifi AP, your network switches, your routers, and your firewall, your servers, your datacenter (if you just have small corner in your office, that is still your datacenter, albeit not a very good one), lots and lots of network cables, and with a lot of careful planning from your IT team, together give you the connectivity: your IT infrastructure.

If your organisation is spread over different locations, especially over national boundaries, that adds to the complexity.

It is the IT infrastructure that forms the foundation upon which you build your enterprise systems. Or alternatively, an enterprise can stick to old-school and do everything in thousands and thousand of spread-sheets. That works, up to a certain point. And even that, there is typically a need to share and exchange files.

Complexity may vary, but modern enterprise cannot do away with a good IT Infrastructure. And in todays terms, that goes beyond just your PCs, your spreadsheets, your emails and websites.