Business Intelligence Advantages

A Collections of Data and Things

 

Within seconds, a company executive in the U.S. can know exactly how many parts their global manufacturing plants are producing. A delivery company can tell you exactly to the minute when their truck will be arriving. A utility company can monitor usage across the country and know when it’s reaching a peak. All of this can be done because of the Internet of Things (IoT) and Big Data.

The IoT is basically a collection of Internet - enabled devices or sensors, other than your computer, which are connected to the Internet and can send and receive data. Big data is what you get when all of this information is collected and analyzed.

Devices such as smartphones, scanners, sensors, and GPS can gather and distribute a lot of information. IoT technology allows the input from these devices to be pulled together.
Once it's all been collected, companies can utilize big data analytics tools to improve business operations, manage equipment and people, target marketing and make their business run more effectively and efficiently.

The IoT is forcing people and companies to change the way they look at things. Information is being funneled fast, in large amounts, structured and unstructured and from places we never thought we’d get information from. Refrigerators talking to smartphones for a shopping list, or fitness trackers measuring your burned calories, sensors sending vital health data to doctors to monitor their patient‘s health in real time, and anything else you can imagine. Vendors can then use that information for marketing directly to consumers or provide better and timely service. Inventory in stores could soon be reliant on just a sensor on a shelf that indicates when an item needs to be restocked.

The next step for businesses is to figure out how to make the most of the data pouring in from things like smart meters, devices, and sensors. How is this data going to affect your next business decision and how is it all going to be analyzed?

Companies need to plan for a continuing influx of data as more devices become connected and interconnected. You need the bandwidth to store data, the real-time analytical tools to analyze it, and the ability to monetize it and turn it into something profitable. Without a plan, you could be left behind.

 

Big Data, Big Decisions

Big data. It’s a pretty broad term, but it’s used to describe data sets that are so big or complex that in order to get the most value out of them companies need to use enhanced data applications; and more importantly know how to manage all of the information.

When it comes to big data, it’s not so much about how much you have, but more about what you can do with it. Managing this data means creating a structure that can store, process, and organize large volumes of structured and unstructured data.

For example, a typical bank offers its customers multiple products; a mortgage, car loan, checking account, saving account, credit line, etc.  In today’s economy customers also conduct transactions online and via mobile devices, and provide feedback on services via social media. Should all that data be stored in different places? No, but banks and other firms are starting to recognize that having all that relevant data stored in one place can provide a wealth of insights about their customers, which is critical to better serving their customers and offering them customized products that makes sense. Having that data in one place will enable efficient data management control and a single-client view.

Regardless of the size of your company or the data being brought in, big data can provide a whole new way of approaching big decisions.

A consumer-oriented company can use big data to listen to, learn from, and leverage consumer feedback to produce targeted B-to-C campaigns. All of the feedback collected from social media and surveys allows a company to build and update consumer profiles and then execute personalized marketing and advertising campaigns.

Insight-driven organizations (IDO) need data to drive decisions. A lot of the time, though, there is so much data these organizations don’t even know where to start. It can be a very long journey to take big data and turn it into insight-driven material. As an IDO you need to figure out what insights will be most impactful with your clients. Then you need to know if you have the right data and analytics to create these insights, and if not, how do you go about getting that information? Once those insights are available how do you create a strategy to implement them in day-to-day decisions making?

Regardless of who is using big data or how it’s being used, there are always concerns about security. Most companies don’t have the infrastructure to store big data on their own IT networks, which means they are either going to be using the Cloud or a third party storage. Transferring data out doesn’t mean to companies transfer their liability. With data coming in from all avenues; social media, emails, files, etc., there are more entry points that need to be protected as along with external access points where the data is being housed.

Finding the most accurate and secure way to use big data will lead to better decision making - which will result in more efficient operations, reducing costs, and reducing risks.

On-Site vs. SaaS: Which is Better For BI?

Over the past few years, many small companies have emerged offering fully-hosted business intelligence systems.  Customers, who didn’t have the needed IT resources to devote to the installation and maintenance of their BI environments, jumped on the bandwagon rather quickly.  In response, even the larger BI vendors began offering on-demand versions of their applications, making the market for BI solutions delivered via a Software as a Service (SaaS) model increasingly competitive.

So, which approach is better when it comes to BI?

The truth is, there are pros and cons to each deployment method.

For example, SaaS solutions minimize burden on IT staff, since all software and hardware components are installed and administered by the third-party provider at an off-site location.  Additionally, on-demand BI is more budget-friendly, since it doesn’t require the large initial expenditures that on-site reporting tools do.  Companies pay a reasonable monthly fee, typically based on the number of users or level of system utilization.  But most importantly, hosted business intelligence can be rolled out more rapidly, since many of the technology components have already been deployed at the provider’s site.

But, companies choosing SaaS-based BI do need to have some concerns.  The first is security.  When opting to have their business intelligence environment hosted by a third-party provider, a company is undoubtedly relinquishing a certain amount of control – particularly when it comes to protection of the data associated with the application.  The vendor determines where the hardware is located, who has access to servers, and how data governance and regulatory compliance policies are enforced.

Another potential issue is the lack of vertical expertise among third-party BI solution providers.  In order for business intelligence to be most effective, those who oversee the environment must have in-depth insight into the industry, as well as the horizontal business function, that the application will support.  That’s why analyst Ventana Research recommends that companies closely evaluate each SaaS vendor’s knowledge of their industry, as well as specific business processes and technology best practices, and select one that can address reporting needs as effectively as internal staff would be able to.  Some experts even go as far as to say that companies looking for hosted BI solutions should seek out a provider that has already implemented data models specific to their particular sector.

Yet another drawback is total cost of ownership.  While initial costs are much lower with hosted software, the total expenses incurred over the cost of the application’s lifetime can be significantly greater.  This is especially true if the company will be renting the SaaS solution for a period of five years or more.

And, perhaps the greatest problem is lack of integration.  SaaS-based software of any kind can never be integrated into an existing technology infrastructure in the same way that an on-site solution can.  In the case of BI, this can hinder the end users’ ability to report directly against real-time operational data.

All in all, no one can say for sure whether on-site or SaaS-based business intelligence is better.  The fact of the matter is that what is right for one company may not work for another.  Before selecting a deployment approach, companies should be sure to carefully evaluate the pros and cons of each, and determine which method makes the most sense for them.