Posts Tagged ‘analytics’
As The Internet of Things continues to grow, huge amount of data is going to be generated. How huge is the “huge”? Really huge. I do mean that.
Physical devices across the globe are consuming and creating data to drive a continuously connected world. David Booth, CEO at BackOffice Associates believes that currently we are at the tipping point of the Internet of Things. He says, “It was not a big leap for the industry to realize that an IoT global network of continuously connected devices would mean that data would not only be created at geometric rates, but that it would become one of the most valuable commodities in the world.”
Alongside the fact that year 2016 was declared to be the year of the first Zettabyte in internet traffic, Cisco report says the number will reach 2.3 ZB by 2020. Before long we will be transferring this much data annually.
If it does not say anything to you, imagine a byte equals 1 character of text – a zettabyte would cover War And Peace by Leo Tolstoy(which is about 1,250 pages) at least 325 trillion times. Or if 1 gigabyte can store 960 minutes of music – technically a zettabyte would be able to store just over 2 billion years of music. If that still isn’t illustrative enough, let’s measure in cups of coffee. Cisco states that if the 11oz coffee on your desk equals to one gigabyte, a zettabyte would have the same volume as the Great Wall of China. This amount of information is mind-blowing. Zettabyte transformed Big Data into enormously Big Data.
The Internet of Things (IoT) is expanding rapidly and relentlessly. And as IoT grows, so do the volumes of data it generates. Ignoring this fact is not an option, and companies will do so at their own peril and risk.
Though there are many new start-up companies storing, analyzing and integrating massive amounts of big data created from the IoT, not many of them have actually considered how the IoT can and will transform organization thinking by implementing data quality and information governance.
With so much data being created, companies must understand what they want to do with it, what are their data requirements and ensure that they have access to the right data. Unless a company can find a way to accumulate, manage and, most important, monetize their data storage, data hoarding can be a real issue for them. Put simply, while the value IoT brings is in the information it creates, innovation gold lies in the filtered data an organization has extracted from the intermediate layer between the devices and the cloud (so called “fog”).
Obviously, data provides powerful potential for boosting analytics efforts. And analyzing the amount of data that is going to be created by the Internet of Things requires new, advanced analytic techniques. The good news is, artificial intelligence and cognitive computing are maturing at a fast pace.
When used properly analytics can help organizations translate IoT’s digital data into knowledge that will contribute to developing new products, offerings, and business models. IoT can provide useful insights into the world outside company walls, and help strategists and decision-makers understand their customers, products, and markets more clearly. It can drive so much more — including opportunities to integrate and automate business processes in ways never imagined before.
Rowan Trollope, Senior Vice President and General Manager of Cisco’s Internet of Things (IoT) and Applications, told participants at the Cisco Live conference, “One of the biggest mistakes you could make now is to underestimate the Internet of Things. This is a life or death issue for most of our customers. They have seen what has happened with Uber and taxi companies and with Netflix and Blockbuster”.
The bottom line is that IoT and Big Data can either disrupt your business or help you become more competitive compared to other businesses that are about to be disrupted.
Business Development Manager
Professional Software Development
When a technical term is used more and more frequently the exact definition becomes “blurred” and its true meaning is usually greatly distorted.
This what happened to the term ‘business intelligence’ or BI. Ever since, when the term had only appeared, the development of technologies has substantially expanded our understanding of BI and of what advantage and benefit the company can retrieve from their available data.
So, what does ‘business intelligence’ mean today? How it could be useful for companies and how to apply its underlying ideas correctly to ensure the steady growth of efficiency and profitability of a business?
What is business intelligence? Why is it important?
BI consists of two completely diverse, but at the same time complementing one another aspects.
- Value for the business.
Implies how companies can use the available information in order to multiply profit and efficiency and bring new products and services to the market successfully.
- IT strategy.
Includes the idea of what technological solutions to apply in order to achieve greatest possible utility of BI.
Presentation of data in a specific format for efficient usage by the company has always been a challenging task. For many organizations, it is quite complex to determine what particular information is required for a specific use.
Such business analysis requires certainty in methodologies and goals.
Earlier BI resources were limited by the lack of available data collection technologies. Nevertheless, modern technologies such as big data, analytics, mobile services and cloud computing in their combination allow obtaining a continuous flow of detailed information quite fast and with no serious investments.
Still, the current bottom line lies in extracting some valuable sense from these data and, in many respects, it is much more complicated than collecting information itself.
Five efficiency criteria of BI-system (and BI-strategy)
1. While selecting a BI-system one should be guided by the real needs of a particular company
The most common and at the same time the most dangerous mistake is when the BI-systems dictate the strategy of their usage. As a result, the company gets plenty of non-synchronized applications, awkward interface and the infrastructure that is already out of date, yet so entrenched in the IT system that could be barely substituted.
2. Be flexible
Flexible model of the integration of the appropriate software involves constant repetition of certain operations with the gradual development of the system. This allows companies to evaluate the success of the project at any point of time, to determine at what stage it is and towards what it moves.
As a rule, creating, testing and integration of BI-technologies goes much more smoothly when the company receives real-time feedbacks from all the running processes and is able to make required adjustments on the fly. It is vital for BI-systems!
3. User-friendly interface
BI-solutions focus on collection, visualization and management of the data.
Usually, when it comes to large amounts of numeric information companies face a risk to get exceptionally technical, inconvenient and incomprehensible data for the “illiterate” users of the system. This information is highly functional, but impractical, especially when it is badly integrated with other applications.
Integration is a key point in deploying BI-technologies. In case the interface is non-intuitive, complex and inconvenient for the end users, BI-system will definitely work inefficiently.
There is a tendency to allocate significant resources for the integration of the latest technologies promising unprecedented results. However, such investments potentially may do more harm than good. Intelligent, targeted and smooth integration is the key to avoid serious errors during implementation.
4. BI is a tool available to everyone
BI has been long used by completely different users, not only by experts with appropriate education and experience. BI-system should be simple and easy to understand to everyone.
For this purpose, companies have to attain the convenience of analytics and the reports drawn on its basis; it should be simple and demonstrative. The collected data should be presented in the way so that any user could easily make definite conclusions.
5. Centralize your data
The desire to achieve the result, based on useful information implies proper data handling. Receiving data from multiple sources and storing it in a centralized information DB, capable of filtering, sorting and removing the unnecessary is critical for the deployment of the applications involved into making business decisions. Apart from that, risk management also becomes more effective through transparency and structure.
General excitement over BI is evident
The role that IT plays in the world has significantly changed over the past few years thanks to the information ‘boom’. Still, construction of a technological infrastructure is not enough for successful data management.
That is why, ‘business intelligence’ it is not just a fashionable term it is a concept that demonstrates the need to move beyond the paradigm of a separate, isolated existence of data analysis and business goals.
In fact, BI reminds us that technologies and business must be closely linked, so that the business goals and business guidelines predetermine the choice of software and, the software in return would provide useful information leading business to success.
Business Development Manager
Professional Software Development