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How Big Data is Empowering Artificial Intelligence and Machine Learning

With the demand for big data services continue to rise, a Big Data Analytics Company UK delivers services that empower to integrate different frameworks, team up information and present it to customers. The service providers in the United Kingdom offer extensive services across all BI or Business Intelligence stack layer, like Data cleansing, data aggregation, database tuning, ETL, data mining, OLAP and more.

HOW BIG DATA EMPOWERS ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
The world is growing at tremendous speed each single moment, and at the same speed is growing the overall size of data all over the world, which constitutes technically the term known as Big Data. Aside from Big Data, another tech revolution that’s taking the world by storm is Artificial Intelligence or AI and machine learning. Simply put, AI and machine learning is a set of technologies, which empower computers and connected machines to learn, evolve and improve upon their own learning via iterating and consistently updating the data bank through human intervention and recursive experiments. Tech giants, data scientists and corporations all throughout the world already are foreseeing big data to make a big difference in the overall artificial intelligence and machine learning environment.

BIG DATA BOOSTS ARTIFICIAL INTELLIGENCE
Machine learning, inherently is defined as an advanced app of AI in interconnected machines as well as peripherals via granting them access to data bases as well as make them learn new things from it by themselves in a programmed way. As data size grows continuously and new grounds are broken in analyzing its implications, it’ becoming much meaningful and contextually relevant for machines to have a better idea of the functions with the help of data and analytics.

BIG DATA HELPS TO EXPAND AI
One of the major concerns that people have on AI nowadays is that it would lessen human requirement in all job sectors since most of the work would be performed by robots and computers that are AI-based in the future. The truth is far from it with the big data would play in the picture. The emotional and sentimental big data analysis would always require human intelligence since machines lack decision-making abilities and emotional intelligence based on sentiments. Consider for instance a data scientist analyzing big data about a pharmaceutical giant, which caters to the needs of the market in Southeast Asia might be able to sense the pharmaceutical prescriptions to be launched in those places, keeping local inhibitions as well as reservations in mind. On the other hand, computer-based big data analysis could never yield such search results that are contextually sensitive. Thus, the growing collaboration between big data and AI would only make way for capable and talented human data scientists to evolve consistently and rise in the market, and through all means would be required in a much bigger number as the apps of these techs gain movement.

AI SOLUTION PROVIDERS AND BIG DATA ANALYTICS COMPANIES TO BENEFIT FROM BIG DATA
At present, the overall size of worldwide markets for AI and machine learning based solutions is limited. With the growing proliferation of big data analysis to AI and machine learning procedures, machines and devices would become smarter and could perform better. This leads to improvement and advancement in AI solutions that would boost market adoption of these solutions, giving rise to a big increase in their demand in the market. With the advent of newer technologies as well as the growing sales of production, prices of AI based solutions will significantly fall. This could result in a massive adoption of the devices in third world countries with diverse cultural, ethnic, religious, linguistic and political inclinations and affiliations. Thus, AI and machine learning solutions to be provided in these markets would have to be differently trained and skilled from each other.

PROGRESS IN BIG DATA AND AI INTEGRATION IN 2018
Industry experts predict a progress in integrating artificial intelligence and big data this year. The most relevant big data trend this year would involve bigger integration with AI, machine learning and data science, but management of metadata and global data fabrics would play a key role as well. AI, particularly data science and machine learning would change the way people acquire, manage and analyze data. These days, because of its complexity, this is done mostly by humans, often developers who are hired form an external service provider. Nonetheless, machine learning and data science are the engines of future data and analytics services. First, it would be more on automating routine and simple tasks such as data extraction. Later on, non-routine and more complex tasks would follow, which will lead to intelligent automation. This potentially would scale organization insights, since it allows more room for analytics that are human-based.

There would be a shift from labor-based services toward machine-based, often being part of a converged analytical solution of services and software or in short ‘servware’. Organizations should introduce testing and review boards on all algorithms, models and data used to build trust.

BETTER OUTCOMES FROM AI AND BIG DATA
Without IA or information architecture, there would be no AI. If organizations have no right infrastructure, it difficult to do AI right. For meaningful results, data should be in an organized state, and the right technology should be put into action. IoT has considerably added to data challenges by pressuring enterprises to ingest massive amounts of data at unbelievably high speeds in a short amount of time. This puts a strain on most organizations. Managing metadata plays a role. This kind of governance is necessary for regulatory compliance and self-service access to data.

The world is moving from Big Data to all data, unstructured, structured and contextual, from sources like social, sensors, chat and video. This year, AI would have a much bigger role to play in the preparation of data.

This was posted in Bdaily's Members' News section by Nishtha Singh .