Article | February 19, 2020
With the increasing amount of data in modern businesses, data science has been receiving a lot of attention. A growing number of companies are, nowadays investing in data science researchers and experts to implement technologies like artificial intelligence and machine learning in their organisation in order to derive actionable insights. But, to place such a massive transformation in an organisation, one has to ensure complete business readiness for data science. Although it is interesting to imagine the potential benefits data science can provide for your organisation, it is worth evaluating how much your organisation is prepared to accommodate a team of data scientists.
Article | November 20, 2020
As smart machines, data, and algorithms usher in dramatic technological transformation, its global impact spans from cautious optimism to doomsday scenarios. Widespread transformation, displacement, and disaggregation of world labor markets is speculated in countries like India, with an estimated 600 million workforce by 2022, as well as the global labor market. Even today, we are witnessing the resurgence of 'hybrid' jobs where distinctive human abilities are paired with data and algorithms, and 'super' jobs that involve deep tech. Our historical response to such tectonic shifts and upheavals has been predictable so far - responding with trepidation and uncertainty in the beginning followed by a period of painful transition. Communities and nations that can sense and respond will be able to shape social, economic, and political order decisively. However, with general AI predictably coming of age by 2050-60, governments will need to frame effective policies to respond to their obligations to their citizens. This involves the creation of a new social contract between the individual, enterprise, and state for an inclusive and equitable society.
The present age is marked by automation, augmentation, and amplification of human talent by transformative technologies. A typical career may go through 15-20 transitions. And given the gig economy, the shelf-life of skills is rapidly shrinking. Many agree that for the next 30 years, the nature and the volume of jobs will get significantly redefined. So even as it is nearly impossible to gaze into the crystal ball 100 years later, one can take a shot at what jobs may emerge in the next 20-30 years given the present state. So here is a glimpse into the kind of technological changes the next generation might witness that will change the employment scenario:
RESTORATION OF BIODIVERSITY
Our biodiversity is shrinking frighteningly fast - for both flora and fauna. Extinct species revivalists may be challenged with restoring and reintegrating pertinent elements back into the natural environment. Without biodiversity, humanity will perish.
Medicine is rapidly getting personalized as genome sequencing becomes commonplace. Even today, Elon Musk's Neuralink is working on brain-machine interfaces. So you may soon be able to upload your brain onto a computer where it can be edited, transformed, and re-uploaded back into you. Anti-aging practitioners will be tasked with enhancing human life-spans to ensure we stay productive late into our twilight years. Gene sequencers will help personalize treatments and epigenetic therapists will manipulate gene expression to overcome disease and decay. Brain neurostimulation experts and augmentationists may be commonplace to ensure we are happier, healthier, and disease-free. In fact, happiness itself may get redefined as it shifts from the quality of our relationships to that between man-machine integration.
THE QUANTIFIED SELF
As more of the populace interact and engage with a digitized world, digital rehabilitators will help you detox and regain your sense of self, which may get inseparably intertwined with smart machines and interfaces.
DATA-LED VALUE CREATION
Data is exploding at a torrid pace and becoming a source of value-creation. While today's organizations are scrambling to create data lakes, future data-centers will be entrusted with sourcing high-value data, securing rights to it, and even licensing it to others. Data will increasingly create competitive asymmetries amongst organizations and nations. Data brokers will be the new intermediaries and data detectives, analysts, monitors or watchers, auditors, and frackers will emerge as new-age roles. Since data and privacy issues are entwined together, data regulators, ethicists, and trust professionals will thrive. Many new cyber laws will come into existence.
HEALING THE PLANET
As the world grapples with the specter of climate change, our focus on sustainability and clean energy will intensify. Our landfills are choked with both toxic and non-toxic waste. Plastic alone takes almost 1000 years to degrade, so landfill operators will use earthworm-like robots to help decompose waste and recoup precious recyclable waste. Nuclear fusion will emerge as the new source of clean energy, creating a broad gamut of engineers, designers, integrators, architects, and planners around it. We may even generate power in space. Since our oceans are infested with waste, a lot of initiatives and roles will emerge around cleaning the marine environment to ensure natural habitat and food security.
TAMING THE GENOME
As technologies like CRISPR and Prime-editing mature, we may see a resurgence of biohackers and programmable healthcare. Our health and nutrition may be algorithmically managed. CRISPR-like advancements will need a swathe of engineers, technicians, auditors, and regulators for genetically engineered health that may overcome a wide variety of diseases for longer life-expectancy.
THE RISE OF BOTS
Humanoid and non-humanoid robots will need entire workforce ecosystems around them spanning from suppliers, programmers, operators, and maintenance experts to ethicists and UI-designers. Smart robot psychologists will have to counsel them and ensure they are safe and friendly. Regulators may grant varying levels of autonomy to robots.
DATA LOADS THE GUN, CREATIVITY FIRES THE TRIGGER
Today's deep-learning Generative Adversarial Networks (GANs) can create music like Mozart and paintings like Picasso. Such advancements will give birth to a wide array of AI-enhanced professionals, like musicians, painters, authors, quantum programmers, cybersecurity experts, educators, etc.
FROM AUGMENTATION TO AUTONOMY
Autonomous driving is about to mature in the next few years and will extend to air and space travel. Safety will exceed human capabilities and we may soon reach a state of diminishing returns where we will employ fewer humans to prevent mishaps and unforeseen occurrences. This industry will need supportive command center managers, traffic analyzers, fleet managers, and people to ensure onboarding experience.
BLOCKCHAIN BECOMES PERVASIVE
Blockchain will create a lot of jobs for its mainstream and derivative applications. Even though most of its present applications are in Financial Services, Supply Chain, and Asset Management industries, very soon its adoption and integration will be a lot more expansive. Engineers, designers, UI/UX experts, analysts, auditors, and regulators will be required to manage blockchain-related applications. With Crypto being one of its better-known applications, a lot of transaction specialists, miners, insurers, wealth managers, and regulators will be needed. Crypto exchanges will come under the purview of the regulatory framework.
3D PRINTING TURNS GAME-CHANGER
Additive manufacturing, also popularly called 3D printing, will mature in its precision, capabilities, and market potential. Lab-grown, 3D-printed food will be part of our regular diet. Transplantable organs will be generated using stem cell research and 3D printing. Amputees and the disabled will adopt 3D-printed limbs and prosthetics. Its applications for high-precision reconstructive surgery are already commonplace. Pills are being 3D printed as we speak. So again, we are looking at 3D printers, operators, material scientists, pharmacists, construction experts, etc.
THE COLONIZATION OF OUTER SPACE
Amazon's Blue Origin and Elon Musk's SpaceX signal a new horizon. As space tech gets into a new trajectory, a new breed of commercial space pilots, mission planners, launch managers, cargo experts, ground crew, experience designers, etc. will be required. Since we have ravaged the limited resources of our planet already, mankind will need to venture into asteroid mining for rare and precious metals. This will need scouts and surveyors, meteorologists, remote bot operators, remotely managed factories, and whatnot.
THE HYPER-CONNECTED WORLD
By 2020, we already have anywhere between 50-75 billion connected devices. By 2040, this will likely swell to more than 100 trillion sensors that will spew out a dizzying volume of real-time data ready for analytics and AI. A complete IoT system as we know it is aware, autonomous, and actionable, just like a self-driving car. Imagine the number of data modelers, sensor designers and installers, signal architects and engineers that will be needed. Home automation will be pervasive and smart medicines, implants, and wearables will be the norms of the day.
DRONES USHER IN DISRUPTION
Unmanned aerial and underwater drones are already becoming ubiquitous for applications in aerial surveillance, delivery, and security. Countries are awakening to their potential as well as possibilities of misuse. Command centers, just like that for space travel, will manage them as countries rush to put in a regulatory framework around them. An army of designers, programmers, security experts, traffic flow optimizers will harness their true potential.
SHIELDING YOUR DATA
With data come cyber threats, data breaches, cyber warfare, cyber espionage, and a host of other issues. The more data-dependent and connected the world is, the bigger the problem of cybersecurity will be. The severity of the problem will increase manifold from the current issues like phishing, spyware, malware, viruses and worms, ransomware, DoS/ DDoS attacks, hacktivism, and cybersecurity will indeed be big business. The problem is that threats are increasing 10X faster than investments in this space and the interesting thing is that it is a lot more about audits, governance, policies, and compliance than technology alone.
FOOD-TECH COMES OF AGE
As the world population grows to 9.7 billion people in 2050, cultured food and lab-grown meat will hit our tables to ensure food security. Entire food chains and value delivery networks will see an unprecedented change. Agriculture will be transformed with robotics, IoT, drones, and the food-tech sector will take off in a big way.
QUANTUM COMPUTING SOLVES INTRACTABLE PROBLEMS
Finally, while the list is very long, let’s touch upon the advent of qubits, or Quantum computing. With its ability to break the best encryption on the planet, the traditional asymmetric encryption, public key infrastructure, digital envelopes, and digital certificates in use today will be rendered useless. Bring in the quantum programmers, analysts, privacy and trust managers, health monitors, etc.
As we brace for the world that looms large ahead of us, the biggest enabler that will be transformed itself will be Education 4.0. Education will cease to be a phase in your life. Life-long interventions will be needed to adapt, impart, and shape the skills of individuals that are ready for the future of work. More power to the people!
Article | June 18, 2021
Data is an important asset. Data leads to innovation and organizations tend to compete for leading these innovations on a global scale. Today, every business requires data and insights to stay relevant in the market. Big Data has a huge impact on the way organizations conduct their businesses. Big Data is used in different enterprises like travel, healthcare, manufacturing, governments, and more. If they need to determine their audience, understand what clients want, forecast the needs of the customers and the clients, AI and big data analysis is vital to every decision-making scenario. When companies process the collected data accurately, they get the desired results, which leads them to their desired goals.
The term Big Data has been around since the 1990s. By the time we could fully comprehend it, Big Data had already amassed a huge amount of stored data. If this data is analyzed properly, it would reveal valuable industry insights into the industry to which the data belonged.
IT professionals and computer scientists realized that going through all of the data and analyzing it for the purpose was too big of a task for humans to undertake. When artificial intelligence (AI) algorithm came into the picture, it accomplished analyzing the accumulated data and deriving insights. The use of AI in Big Data is fundamental to get desired results for organizations.
According to Northeastern University, the amount of data in the world was 4.4 zettabytes in 2013. By of 2020, the data rose to 44 zettabytes.
When there is this amount of data produced globally, this information is invaluable to the enterprises and now can leverage AI algorithms to process it. Because of this, the companies can understand and influence customer behavior. By 2018, over 50% of countries had adopted Big Data.
Let us understand what Big Data, convergence of big data and AI, and impact of AI on big data analytics.
Understanding Big Data
In simple words, Big Data is a term that comprises every tool and process that helps people use and manage vast sets of data. According to Gartner, Big Data is a “high-volume and/or high-variety information assets that demand cost-effective, innovative forms of information processing to enable enhanced insight, decision-making, and process automation.”
The concept of Big Data was created to capture trends, preferences, and user behavior in one place called the data lake. Big Data in enterprises can help them analyze and configure their customers’ motivations and come up with new ideas for the creation of new offerings. Big Data studies different methods of extracting, analyzing, or dealing with data sets that are too complicated for traditional data processing systems. To analyze a large amount of data requires a system designed to stretch its extraction and analysis capability.
Data is everywhere. This stockpile of data can give us insights and business analytics to the industry belonging to the data set. Therefore, the AI algorithms are written to benefit from large and complex data.
Importance of Big Data
Data is an integral part of understanding customer demographics and their motivations.
When customers interact with technology in active or passive manner, these actions create a new set of data. What contributes to this data creation is what they carry with them every day - their smartphones. Their cameras, credit cards, purchased products all contribute to their growing data profile. A correctly done analysis can tell a lot about their behavior patterns, personality, and events in the customer’s life. Companies can use this information to rethink their strategies, improve on their product, and create targeted marketing campaigns, which would ultimately lead them to their target customer.
Industry experts, for years and years, have discussed Big Data and its impact on businesses. Only in recent years, however, has it become possible to calculate that impact. Algorithms and software can now analyze large datasets quickly and efficiently.The forty-four zettabyte of data will only quadruple in the coming years. This collection and analysis of the data will help companies get the AI insights that will aid them in generating profits and be future-ready.
Organizations have been using Big Data for a long time. Here’s how those organizations are using Big Data to drive success:
Answering customer questions
Using big data and analytics, companies can learn the following things:
• What do customers want?
• Where are they missing out on?
• Who are their best and loyal customers?
• Why people choose different products?
Every day, as organizations gather more information, they can get more insights into sales and marketing. Once they get this data, they can optimize their campaigns to suit the customer’s needs. Learning from their online habits and with correct analysis, companies can send personalized promotional emails. These emails may prompt this target audience to convert into full-time customers.
Making confident decisions
As companies grow, they all need to make complex decisions. With in-depth analysis of marketplace knowledge, industry, and customers, Big Data can help you make confident choices. Big Data gives you a complete overview of everything you need to know. With the help of this, you can launch your marketing campaign or launch a new product in the market, or make a focused decision to generate the highest ROI. Once you add machine learning and AI to the mix, your Big Data collections can form a neural network to help your AI suggest useful company changes.
Optimizing and Understanding Business Processes
Cloud computing and machine learning help you to stay ahead by identifying opportunities in your company’s practices. Big Data analytics can tell you if your email strategy is working even when your social media marketing isn’t gaining you any following. You can also check which parts of your company culture have the right impact and result in the desired turnover. The existing evidence can help you make quick decisions and ensure you spend more of your budget on things that help your business grow.
Convergence of Big Data and AI
Big Data and Artificial Intelligence have a synergistic relationship. Data powers AI. The constantly evolving data sets or Big Data makes it possible for machine learning applications to learn and acquire new skills. This is what they were built to do. Big Data’s role in AI is supplying algorithms with all the essential information for developing and improving features, pattern recognition capabilities.
AI and machine learning use data that has been cleansed of duplicate and unnecessary data. This clean and high-quality big data is then utilized to create and train intelligent AI algorithms, neural networks, and predictive models.
AI applications rarely stop working and learning. Once the “initial training” is done (initial training is preparing already collected data), they adjust their work as and when the data changes. This makes it necessary for data to be constantly collected.
When it comes to businesses using this technology, AI helps them use Big Data for analytics by making advanced tools accessible and obtainable to help users gain insights that would otherwise have been hidden in the huge amount of data. Once firms and businesses gain a hold on using AI and Big Data, they can provide decision-makers with a clear understanding of factors that affect their businesses.
Impact of AI on Big Data Analytics
AI supports users in the Big Data cycle, including aggregation, storage, and retrieval of diverse data types from different data sources. This includes data management, context management, decision management, action management, and risk management.
Big Data can help alert problems and help find new solutions and get ideas about any new prospects. With the amount of information stream that comes in, it can be difficult to determine what is important and what isn’t. This is where AI and machine learning come in. It can help identify unusual patterns in the processes, help in the analysis, and suggest further steps to be taken.
It can also learn how users interact with analytics and learn subtle differences in meanings or context-specific nuances to understand numeric data sources. AI can also caution users about anomalies, unforeseen data patterns, monitoring events, and threats from system logs or social networking data.
Application of Big Data and Artificial Intelligence
After establishing how AI and Big Data work together, let us look at how some applications are benefitting from their synergy:
Banking and financial sectors
The banking and financial sectors apply these to monitor financial marketing activities. These institutions also use AI to keep an eye on any illegal trading activities. Trading data analytics are obtained for high-frequency trading, and decision making based on trading, risk analysis, and predictive analysis. It is also used for fraud warning and detection, archival and analysis of audit trails, reporting enterprise credit, customer data transformation, etc.
AI has simplified health data prescriptions and health analysis, thus benefitting healthcare providers from the large data pool. Hospitals are using millions of collected data that allow doctors to use evidence-based medicine. Chronic diseases can be tracked faster by AI.
Manufacturing and supply chain
AI and Big Data in manufacturing, production management, supply chain management and analysis, and customer satisfaction techniques are flawless. The quality of products is thus much better with higher energy efficiency, reliable increase in levels, and profit increase.
Governments worldwide use AI applications like facial recognition, vehicle recognition for traffic management, population demographics, financial classifications, energy explorations, environmental conservation, criminal investigations, and more.
Other sectors that use AI are mainly retail, entertainment, education, and more.
According to Gartner’s predictions, artificial intelligence will replace one in five workers by 2022. Firms and businesses can no longer afford to avoid using artificial intelligence and Big Data in their day-to-day. Investments in AI and Big Data analysis will be beneficial for everyone. Data sets will increase in the future, and with it, its application and investment will grow over time. Human relevance will continue to decrease as time goes by.
AI enables machine learning to be the future of the development of business technologies. It will automate data analysis and find new insights that were previously impossible to imagine by processing data manually. With machine learning, AI, and Big Data, we can redraw the way we approach everything else.
Frequently Asked Questions
Why does big data affect artificial intelligence?
Big Data and AI customize business processes and make better-suited decisions for individual needs and expectations. This improves its efficiency of processes and decisions. Data has the potential to give insights into a variety of predicted behaviors and incidents.
Is AI or big data better?
AI becomes better as it is fed more and more information. This information is gathered from Big Data which helps companies understand their customers better. On the other hand, Big Data is useless if there is no AI to analyze it. Humans are not capable of analyzing the data on a large scale.
Is AI used in big data?
When the gathered Big Data is to be analyzed, AI steps in to do the job. Big Data makes use of AI.
What is the future of AI in big data?
AI’s ability to work so well with data analytics is the primary reason why AI and Big Data now seem inseparable. AI machine learning and deep learning are learning from every data input and using those inputs to generate new rules for future business analytics.
"name": "Why does big data affect artificial intelligence?",
"text": "Big Data and AI customize business processes and make better-suited decisions for individual needs and expectations. This improves its efficiency of processes and decisions. Data has the potential to give insights into a variety of predicted behaviors and incidents."
"name": "Is AI or big data better?",
"text": "AI becomes better as it is fed more and more information. This information is gathered from Big Data which helps companies understand their customers better. On the other hand, Big Data is useless if there is no AI to analyze it. Humans are not capable of analyzing the data on a large scale."
"name": "Is AI used in big data?",
"text": "When the gathered Big Data is to be analyzed, AI steps in to do the job. Big Data makes use of AI."
"name": "What is the future of AI in big data?",
"text": "AI’s ability to work so well with data analytics is the primary reason why AI and Big Data now seem inseparable. AI machine learning and deep learning are learning from every data input and using those inputs to generate new rules for future business analytics."
Article | February 27, 2020
Microsoft recently announced that it’s leveraging a new global strategic partnership with Telefonica to jointly develop “go-to-market plans for regions the company does business.Last year during Mobile World Congress 2019, Microsoft took the veil off its newfound relationship with the international telecommunications giant, Telefonica.Highlighted during this year’s announcement was Microsoft’s opening of a new datacenter region in Spain. Microsoft’s new data center comes at a time where the company looks to help expedite Spain’s digital transformation.