Data is the currency of business in today’s digital business era. The data authority companies helping customers leverage and manage their data wherever it resides in the cloud, in their data centres, or at the edge as part of the Internet of Things (IoT). The more you torture the data, the better it gets. It is like torturing data more and more gives you the ability to get it to confess, what you like to see.
Data Data Data !!!!
Organising data the Concealed-Weapon in particular data framework as simple but time taking task. For businesses to organise and understand their data assets is easy to make use. Sadly most of the time data is even not touched. Today’s data has an answer for most of the things if not everything. Data of today can be quantified and tracked easily as it has human elements. What this means –
- What will the temperature be next day or week or even one a particular day in future?
- How my follower’s trend may look like in the next 3 months?
- How the health of the person would be based on data and environment?
- How many sales will be in next month?
If we talk about the sudden jump in mobile data usage then it clearly points out the cause of a new generation of networks. Now adding AI flavours on top is making it more interesting. Point to make a note with clear understanding is “The change or technology shift that 5G and subsequent technologies will bring will not be the same as from 3G to 4G”. The powerful combination of mobile data, artificial intelligence and machine learning algorithms will become the key driver for growth in data usage. Mobile Data – Who moved my cheese? this title would fit more for subscribers thereafter.
Neural Interconnected Networks – The Fusion of Mobile Data (Internet) & AI
In the next upcoming wireless generation (5G onward) the internet with the use of artificial intelligence will penetrate the internet of things on blockchain-based security. This fusion will also penetrate big data analytics with machine learning algorithms and going to transform the internet and its usage to a level which is difficult to predict today.
The companies which are still not open to welcome and adopt changes brought through new electricity called Artificial Intelligence will slowly die because of no power. Quantum computing will add more power in AI and next generations wireless networks.
The Fusion of Mobile Data (Internet) & AI – The AI-based Internet or AI internet is emerging, this is also bringing clarity and connecting dots between virtual reality and the physical world. The way we lived 10 years back, today and 10 years after will never be the same even to single-digit lifestyle. We are learning new things and will continue to do so at a much higher pace. AI has already made its place permanent in our lives.
Almost all the business have realised this and now adapting to survive be it banking, telecommunication, finance,, healthcare, agriculture, education, or even governmental departments. The biggest win will come from neural networks in the security domain.
It would not be wrong . to say the internet will become business as usual and essential commodity of human life like water, air and food. 5G & 6G (still a concept) with a combination of AI will be able to make a real-time decision on where to serve data bandwidth more and where to cut down. 5G looks promising in terms of speeds which will be up to 100 times faster and a response time up to 20 times faster as compared to 4G. There is no reason for this to happen without devices starts sensing and thinking with AI as a backbone.
The Live Experience
Last month I was at a big retail store in Harare and it was a very busy day due to the fact it was month-end and people got paid. Grocery shopping was in full swing, I also bought some groceries for my self. When I was in the queue for payment and collection. I saw almost everyone making payment either by swiping the magic plastic card or by moving fingers on their smartphones. The electronic payment queue was moving fast compared to the cash payment queue. Even though it had only a handful of people with just one/two small item/items.
The thought came to my mind out of this whole picture was “What’s happening here besides the payments through mobile and plastic”? Understanding the data you have is a good first step in knowing what you can do with it. Data, More Data, Lots of Data so-called BIG DATA was getting generated. Customers’ attitude and habit can be known by customer ratings or customer comments as our data source. Artificial intelligence and big data are like 2 sides of the coin, and they need each other to ring to fruition what both are promising. Big data is the key to data-driven decisions and discovery.
Generate Data & Collect Data
As on date we see data almost every single person, company or any entity is just running after data. With a combination of all disparate data and predictive analytics, one can create highly accurate data models. Depending upon data nature relevant prediction can be made. For example, if data was related to pollution trends then in advance allowing civic agencies can make relevant predictions and changes to prevent pollution spikes and keep its level in order.
Big data and analytics can also help improve traffic management in addition to just monitoring pollution levels. Fates of artificial intelligence and big data are intertwined though.
Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. In the past, storing it would’ve been a problem – but new technologies (such as Hadoop) have eased the burden. A comprehensive and widespread network such as this to track the causes of pollution at source will allow government agencies to create smarter strategies to combat pollution – and when combined with predictive analytics, predictions in some cases can even be made in advance to assess your Big Data analytics needs.
World Wide Data Wrestling – Concealed-Weapon
The importance of data doesn’t revolve around how much data you have, but what you do with it. Analytics predictions and priorities for 2018 or in other word “The age of algorithms” is upon us already. Data is coming up as second costliest item after fuel. Data characteristics like volume, velocity, variety, variability and complexity. The concept gained momentum in the early 2000s when industry analysts articulated which is now the mainstream definition of big data as v’s and c’s. Cloud computing and other flexible resource allocation arrangements.
Data or Concealed-Weapon for a better name can be generated from any source to analyze for any reason. To find answers for cost or time reductions, new product development, optimized offerings or even for smart decision making. Combining data with high-powered analytics can accomplish business-related tasks. Big Data can be used for Small Business i.e micro-credit or even for microinsurance. Parallel processing, clustering, MPP, virtualization, large grid environments, high connectivity and high throughputs identify strengths and gaps in data collection efforts. Kind or type can be put up in many buckets i.e structured data or unstructured data, internal data or external data and human-generated or machine-generated data i.e tweets, retweets, facebook likes etc.
More and more data also comes with more and more risks and keep costing the industry millions or even billions of dollars. Without the right security and encryption solution in place; big data is a very big problem.
A smart Big Data factory should take a smart approach to this costly, sensitive and critical asset maintenance and management. Before we go further let me explain in short what is Big Data. The quality of any analysis is dependent on the quality of the data. Due to the nature of the data might be more reliable and valid than customer sentiment metrics from social media content; as a result, the use of structured data might lead to a better understanding of your data.
I am sure most of us know the answer already; Big data is a term that means a huge amount of Digital Data. This data is unorganized and unstructured because it is captured from different sources. So it is difficult to analyse. For instance, cardholder data should be managed in a highly secured data vault, using multiple encryption keys with split knowledge and dual/triple control. Affordable open source, distributed big data platforms, such as Hadoop.
DataIntelligence – the Biggest source of a security breach
Big data presents a tremendous opportunity for enterprises across multiple industries especially in the tsunami-like data flow industry of “Payments”. FinTech, InsureTech, MedTech are major data generating industries i.e a massive group of factories. According to some data from Google, it shows technology-based innovative insurance companies pays $0.60-$0.65 of each dollar in claims, with the rest covering costs of admin, marketing and reinsurance. Next questions were “Who owns this data?”, “What is the use of this data?” and “How secure is this data?”.
My payment data with all my sensitive information is it secured and in safe hands? Mobile Money vs Mobile Banking difference is same with data mining and data drilling. What about the privacy of my sensitive information?. Thousands of questions started spinning my head. There is a massive scope of big data security.
This presents a significant opportunity for disruption. With improvements in technology which anyways happening every day without demand and this will bring a reduction in each of these cost items. Consequently, the data sources being compiled need to be secured in order to address security policies and compliance mandates. It’s important to remember that the primary value from big data comes not from the data in its raw form, but from the processing and analysis of it and the insights, products, and services that emerge from the analysis.
Data Sources – Social & Other Platform
The sources for big data generally fall into one of three categories i.e Streaming data – Data as a Concealed-Weapon to IT systems from a web of connected devices. Social media data – The data on social interactions and finally publicly available sources – Data are available through open data sources like government etc. After identifying all the potential sources of data decisions needs to be made for harnessing information i.e How to store and manage it, How much of it to analyze and How to use any insights you uncover.
Further, more data sources are added all the time. Start and grow businesses and prevent frauds by taking security before innovation. Transactions and data generated out of them will then be safe, quick and easy. Such data require best technologies that help to make the most of data and big data analytics with cheap and abundant storage, faster processors etc.
As organizations undertake data-driven digital transformation. To achieve the same they are increasingly turning to powerful artificial intelligence and deep learning capabilities to drive competitive advantage. Fully enabling that opportunity requires the ability to easily integrate and manage data at scale from diverse sources, and to support the demanding performance requirements of AI/DL applications.
Robots can fail; as reason is very simple and known which is machine learning models are not sufficiently accurate or can’t be accurate without lots of data and lots of training. Artificial Intelligence with cloud computing adds advancements using new use cases to improvise the systems developed so far.
Points to Note:
AI and ML are now making the most powerful tools in a marketer’s arsenal for improving return on investments. All credits if any remains on the original contributor only. We have covered all basics around data models or the importance of data. In the next upcoming post will talk about implementation, usage and practice experience for markets.
Books + Other readings Referred
- Research through open internet, news portals, white papers, notes made at knowledge sharing sessions and from live conferences & lectures.
- Lab and hands-on experience of @AILabPage (Self-taught learners group) members.
Feedback & Further Question
Do you have any questions about AI, Machine Learning, Data billing/charging, Data Science or Big Data Analytics? Leave a question in a comment section or ask via email. Will try best to answer it.
Conclusion – In my personal opinion and hand-on experience Data helps business and works as the biggest influencer for Blue Ocean shift strategy. So I say Data is the angle to show you the best of your business’s hidden potential. In short, big data as Concealed-Weapon has transformed Artificial Intelligence, to an almost unreasonable level. Blockchain technology could transform AI too, in its own particular ways but for now, that’s for my next post. I guess my analysis is reasonable but conclusion at this time might be a bit pre-mature. The clearing houses get real-time payment data to apply their expertise also have a vision beyond their current rails and the pockets to support it.
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