2017 was the golden phase for cryptocurrency generated from blockchain technology. It is mind-blowing to see how a hasty increase in the demand of blockchain technology has been. Well, the reason being that the developers found unnecessary requirement of third parties such as banks to reduce transaction fees. With higher development and research in the technology, blockchain has a far wider application today, moving beyond just transactions and cryptocurrency.
Money Transfers and Payment Processing Typically, blockchain has been in use for transfer of digital funds or currencies from one party to another without any cyber risks. Usually, most of the transactions processed via blockchain can be completed within seconds thus making it very fast. Retail Loyalty Rewards Campaigns Blockchain can be used as go-to for the loyalty rewards for the customers. Create a token-based system to store the tokens within the blockchain technology to give them incentives. This will help any retailer to gain loyal customers while eliminating fraud and cumbersome paper-work. Digital Identities Microsoft is looking for a solution to deal with the face identity challenges. Experts at Microsoft are therefore, planning to create a decentralized digital ID to allow users a way to access their digital identities. Data sharing In November, Cryptocurrency IOTA launched a beta version for its data marketplace for easy trade of unused data. Therefore, blockchain can help in storing and accessing the unused data to utilize it in a better way. Monitor Supply Chains When it comes to monitor supply chains, blockchain has shown a remarkable scope. It will eliminate paper-based trails to make the supply chain process efficient while tracking goods in real time. Blockchain has given developers a possibility of real time transactions, eliminating pilfering transaction fees, and transaction settlement in few seconds. Developers at Sphinx Worldbiz are working tirelessly to unfurl more scope to deal with the current and future market challenges with blockchain. SOURCE: Where can Blockchain be used?
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Ever searched for a product or service and later seen an advertisement popping up on your Facebook news feed? If yes, then congratulations, you have been re-targeted. It shouldn’t be a surprise as companies collect data to target their audiences for better customer relations with the help of Big Data.
Big Data has gained lot of traction but, are you really clear about the meaning of these two words? How it is impacting our daily lives and why big firms are using it? To put it simply, Big Data is a large set of unorganized data that are computationally analyzed to unfurl the trends and patterns on a certain subject. From small firms to established enterprises, the process has become one of the most promising technologies of the epoch. It is surprising to note that in every two days we create as much information as we did until 2003 and over 90% of all the data globally is created in just past two years. It is mind-blowing to see how big data is increasingly becoming the backbone of every industrial sector. Meanwhile, people are looking for the answer if big data will grow or fall behind in the coming times? Let’s dig deeper and look at the possible trends for Big Data in the coming years. Data Silos will Continue to Boom When Hadoop boomed five years ago, there was a possibility to consolidate all the data onto a single platform regardless its nature- analytical and transactional workloads. However, the prediction panned out in the presence of many challenges. One of the biggest challenges was the different data types that require different storage units. From relational database, HDFS, object stores to time-series databases, all have their own obstacles. Therefore, it will become complex for developers in maximizing strengths while packing all the data into one size. However, cloud data stores like Hadoop and S3 are helping companies to store their data in a cost-effective manner. But that doesn’t mean data silos will decrease especially in the absence of strong centralizing force. So, we might have to get used to it! Enhanced Data Retention Policies According to Carlos M. Meléndez, chief operating officer at AI consulting firm Wovenware, it is not essential to store every data forever. Only some needs storage for some time. Coming years will focus on machine learning in a way that will clean and protect the integrity of stored data. Also, it will have automated flush feature to dispose such data which is no longer needed. Don’t worry, the data will not be lost forever. You can recover the disposed data anytime as algorithms will be scripted in a manner that the backup feature will be provided. A CIO Showdown As per James Markarian, CTO of SnapLogic, “The days of forgetting that the ‘I’ in CIO stands for ‘information’ are over.” He added that CIO will not only be limited to infrastructure but will also become a process to manage and create strategies for company’s data. By the end of this year, the process will pick up steam due to digitization and data transformation. Skills will be Proliferated as the Tech Evolves As it requires skills and knowledge to manage and run the data in the right stream, thus in coming years, the demand for any individual who can infuse neural network into final production is expected to increase exponentially. There is plenty of scope for folks who have a good knowledge of Matlab, Scala, C, and Java but Python will continue to dominate among all the languages. Meanwhile, data engineers who know Spark, Airflow, and databases will tend to grow. Machine learning engineers will not remain behind in the Big Data world as well. In a Nutshell Indeed, converting huge unorganized data collections into an actionable insight is a complex task. But Big Data experts and industry big-wigs surely see keeping up with the technology to leverage information for better customer relations. Experts are analyzing legit, substantial, ethical and technical hurdles in Big Data and AI processing, but its promising benefits are difficult to ignore. SOURCE: Emerging Big Data Trends to Watch in 2019: Keeping Up or Falling Behind? Artificial Intelligence (AI) as a technology is still in its nascent stages of Narrow AI, however, the application-base has expanded from computers to various other fields of human interaction with technology. One of the notable successes AI has achieved is personalization of customer experiences trough its dynamism. Machine Learning (ML) has proven to be a great way to stay interactive and relevant to its users. Virtual Personal Assistants like Siri, Alexa, Cortana and Echo are living examples of the same. Moving on from computer applications, machines have been made AI sensitive for greater user experience. Smart cars are an example of it. Transportation has been one of the areas where AI can be seen transforming the way people travel in future. Artificial Intelligence (AI) is revolutionizing driving, making transportation more efficient and safer and as exciting as any other car is. Marketing is yet another area where AI and ML can be found leaving their imprint by predictive analyses which helps companies identify the typical and general customer behavior. It allows the marketers to up-scale their content marketing strategies for better optimization and eventual ROI. Healthcare is hugely benefiting from AI. The technology uses software and complex algorithms to analyze human medical data, thus helping in diagnosis, the treatment, see the patient outcomes and provide a well-defined output to the patients. ML algorithms are responsible for this. There are many other industrial and technological benefits achieved using AI including service industries, manufacturing industries, cognitive computing, robotics, and a lot more and this is just the tip of the ice-berg. SOURCE: Successful Applications of AI Blockchain is a revolutionary digital payment technology still in its nascent stage. To simply put it, blockchain contains digital payment information in block forms that does not allow hackers to steal your data in any way possible.
Top Programming Languages Best for Blockchain: C++ It is the most preferred blockchain programming language as it offers advanced multi-threading potentials, access over memory, and semantics. It also bids object-oriented features such as function overloading and runtime polymorphism to perfectly link the data together. Python This language is fairly new but hyping the world of programming hastily. The language is viably preferred in the blockchain industry as it can perform many tasks with just single command. Solidity Influenced by PowerShell, JavaScript, and C++, Solidity is a high-level language used to implement smart contracts on multiple blockchain platforms. The language is very popular amongst Ethereum developers. Java Due to its highly-potential portability, Java is valued in the blockchain industry. Java and C++ have many similar features as they both are object and procedural-oriented programming languages. It has almost 9 million developers across the world. NEM’s basic blockchain network has been written in Java only. Ruby Although the oldest programming language, Ruby made its comeback with the blockchain technology. It allows users to use a perfect blend on different languages to develop the ideal blockchain. The language gives the access to make amendments if required. While developing a blockchain, the right programming language is the key to safeguard cyber security. The expert programmers at Sphinx Worldbiz offer ideal solutions to befit your complex requirements SOURCE: Which programming language is best for Blockchain? |
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September 2019
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