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Certified Big Data Analyst (CBDA)

Companies spanning across all industrial domains are experiencing a Big Data Boom! Several databases of digitally stored information and expert knowledge await us. Before the huge wave of digital data turn intimidating, we are saddled with a much-valued responsibility of managing the raw data. With computational powers growing at a spectacular speed, mastering this data-centric world can be challenging as well as fun. Big Data is to Artificial Intelligence what Automation and Robotics is to Internet of Things (IoT).
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Why Big Data?

The pace of digital content generation is expected to be over 30 times in the next decade with major businesses around the world generating and consuming both structured and unstructured data.

Organizations would require information that is inherent in social networking sites, media platforms, websites, analytical applications and data warehousing systems. Such processing involves complex workloads that cannot be handled by existing data management techniques and technologies.

Faster, better and cost-effective decisions is what makes businesses successful and unique and Big Data technologies such as Hadoop and cloud-based analytics bring significant advantages while making such decisions.

Big data analytics enables the organizations to handle a wide variety of data using advanced analytical capabilities including event, predictive and text analytics. These new data processing infrastructures includes faster hardware starting with faster multi-core processors and large memory spaces, to solid-state drives and tiered data storage for handling hot and cold data, to bring significant business growth.

With enhanced capabilities resulting from speed, capacity and scalability of cloud storage, Big Data analytics tools continue to improve. As the business intelligence software market matures, Big Data processes will progress to data visualization tools that can provide the competitive edge to the various businesses around the globe!
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Rise of Big Data

In this interconnected world facilitated by digitized communication systems, flow of digital data is in abundance and growing at an exponential rate. We have decades of data from healthcare industries, finance, manufacturing, marketing and advertisement and more data streaming through different online channels. Big Data has emerged as the most effective way to manage this treasury of information and derive better and efficient systems for our future society. Big Data systems are all set to conquer the field with Data Structuring, Data Serialization, Batch Processing, Cluster Computing, Data Mining, ETL and Data Warehousing techniques, adopted by companies like Microsoft, IBM, Intel, Google, Oracle, CISCO, Amazon and so on.

Ring in the Future

Apple’s Siri, Amazon’s Alexa and Google’s Assistant have offered you comforts that you had not imagined so far. Privileges that would define the comforts of your personal life in the future, will undergo a transformation. And the world around you would not stop at empowering you either with better technologies of smart cities, autonomous cars, LIDAR technology powered mapping and navigation systems and so on. As the machines of the future evolve adding more accomplishments to its list, becoming smarter with machines becomes mandatory.
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Step into the World of Artificial Intelligence

Welcome the surgical robot, da Vinci. It is equipped with surgical instruments, provides a high-definition, magnified, 3D view of the surgical site and aids surgeons to perform surgeries. Virtual nurse assistants Angel and Sensely are AI-powered nurse avatars who can be deployed to patients.

AI farming software The Brain assists in keeping a watch over a farm, monitoring things like nitrogen levels, temperature, and robot location.

Cognitive science and AI are being used to provide personalized tutoring and real-time feedback for post-secondary education students.

Artificial intelligence (AI) can be programmed and train machines to match or even surpass human capabilities. Human concerted efforts in building artificial neural networks enhanced machines’ ability to learn, store and analyze information.
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Big Data Cybernetics

Revolutionizing the healthcare sector, Big Data cybernetics has led to the development of Hybrid Assisted Limb (HAL), the lower-body exoskeleton available in the first licensed cybernetic medical institution in Florida.

Big Data cybernetics has contributed to the motion perception and simulator (MPSim) based on model predictive control concept. The MPSim for example, helps to control a helicopter in real-time.

Big Data cybernetics combines the theoretical and statistical methods to calculate and understand the dynamics between processes based on large data streams.
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Problem Solving the Big Data Way

Game-changer in customer and patient experiences in medical treatment facilities.

Best companion for academic researchers to collaborate with appropriate industry partners to simultaneously achieve both theoretical and practical advances.

Preventive maintenance is another highlight of using Big Data to solve the issues that negatively affect the workflows when equipment is offline or in an emergency. Big Data has simplified the Los Angeles transit system, implemented the San Diego WaterSmart Target program, and helped to create Santa Monica as a Smart City, to mention a few examples of Big Data’s contribution to problem solving.
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Machine Learning

Machine learning algorithms are being applied to data to help automate airline operations. United Airlines in collaboration with Amazon Alexa called United skill provides answers to the most common questions about United flights in natural language.

Machine learning uses Uber Eats to estimate the delivery time for meals by assessing the time to travel between you and the restaurant, the average speed and the time to prepare the meal and using predictive method after analyzing thousands of records.

Machine learning in training huge databases to improve machine perception has powered release of YouTube-8M, a dataset of 8 million YouTube video URLs, along with video-level labels from a diverse set of 4800 Knowledge Graph entities.

With Machine Learning, machines can be made to grow in capacity for logical thinking and reasoning – acquire sensory perceptions and extract patterns from static as well as live streaming data as varied as learning to play a guitar, driving a car, riding a bike, understand a human speech and so on. Machine learning makes it easy to acquire the expertise and store them as codes.
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Deep Learning

Deep Learning Danish software is detecting cardiac arrests by listening to the tone of the voice of a person.

Deep Learning algorithm used by Baidu Research’s is assisting in detection of breast cancer.

NLP algorithms is transforming audio and text data into outputs based on sentiment analysis, speech recognition, speech synthesis, language translation, and natural-language generation.

Knowledge of Deep Learning techniques and frameworks can be applied to multiple domains like financial services, medical imaging, autonomous driving, and others that can unravel a new world of living.
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Big Data & Neural Networks

Complex structures of huge number of datasets containing multidimensional data that represents Big Data, can get strenuous for analysing and visualizing to obtain futuristic results. Neural networks implemented with appropriate algorithms, enable us to easily classify Big Data and train them for use in businesses, healthcare and other sectors.

Early detection of cancer cells is possible with such neural network + Big Data combination.

Recurrent neural networks (RNN) and Artificial neural networks (ANN) are powerful techniques to solve real-world issues concerning pattern recognition, prediction and modelling.

The neural network + Big Data combination is also a catalyst in implementing processes like job scheduling in a public cloud environment such as Amazon Web.
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Big Data Leveling up Efficiency across Industries

Big Data has changed the data analysis landscape with excellent tools such as Hadoop which is an open-source software framework for storing data and running applications in batches. The other popular Big Data tools are Microsoft HDInsight, Polybase, NoSQL, Hive, etc.

Big Data stands to bring higher levels of efficiency for companies in various domains:
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Deloitte claims to make 100,000 legal positions automated by 2036.
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Netflix saved $1 billion by delivering personalized choice of movies and TV shows to the subscribers.
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PayPal applies at least 3 Machine Learning approaches to eliminate risk and fraud.
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Facebook research lab has proved that DL can enhance learning to a degree of 1.3m images an hour though at the cost of supporting 256 Tesla P100 GPUs.
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IBM Watson Genomics, IBM Watson Oncology, Google’s DeepMind Health, MIT Clinical machine Learning Group are a few names taking advantage of ML for better diagnosis of diseases, making right choice of treatment, better research and clinical trials and adopting better techniques of control.
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Amazon Web Services, Finnish company F-sure, IBM Watson and other cyber security companies have begun implementing AI and ML for data mining to predict network intrusions, other malicious activities and eliminating them.
Machines have infringed the boundaries of human cognitive learning by incorporating cognitive processes such as thoughts, attention, memory, perception and language skills to process data based on the environment. It facilitates in finding correlation between data, developing insights based on conditioning and solving problems with higher level intelligence.
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Who Needs to Know Big Data?

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Telecom and Retail industries would benefit from predictive models that help understand consumer behaviors and preferences.
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Salespersons and insurance companies can leverage on the CBDA to know the product usage patterns of their customers.
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Healthcare and public health officers must use CBDA to integrate medical data with individual or collective data to help monitor & predict disease outbreaks and find cures.
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Website owners can easily analyze the volumes of collective data using Big Data tools and algorithms.
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Security and Law enforcement agencies will find RCBDA a boon to detect and prevent fraudulent activities including cyber-crimes.
From business people who need to optimize their business processes & supply chain delivery cycles, to the HR executives who need to augment their talent acquisition, staff management & company objectives, or the R & D professionals who need to analyze huge amounts of data distributed across different network systems, CBDA is THE one-stop solution!
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Big Data Impact

Big Data has in it a huge breakthrough potential that makes it an indispensable part of society progress and innovation. It has changed the way people do business and its applications are bound only by the human imagination. Students, professionals, corporates and businesses can leverage on the predictive analysis and other Big Data techniques to bring in operational efficiency and create a competitive edge regardless of the size of the industry.

The impact of Big Data can be seen in the way it has revolutionized old-school industries. Rolls Royce’s successful integration of Big Data analytics influencing the aircraft engine manufacturing and the world’s largest retailer – Walmart’s using Big Data analytics to transform its retail sector, are just two famous examples of the impact.

The impact of Big Data analytics is such that even before we realized, it has given birth to an entirely new industry! Data no longer serves the sole purpose of being an ancillary to the core business. Companies accessing, storing and processing data, valuing it as an asset and applying Big Data analytics tools has resulted in creating a whole new industry.

Regardless of the size or sector, Big Data analytics is penetrating into every business and systems across the world, creating revolutionary enhancements and is here to stay!
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What is the job role of Big Data Analyst?

As a Big Data Analyst, you are the bridge connecting organizations and information processing systems, using data analytics, machine learning and AI to evaluate the technical performance of a company and provide recommendations for smooth system enhancements.

A CBDA is an asset across the industry sectors and can assume various roles such as Data Scientists, Data Architects, Data Miners and so on.

The key functions of the CBDA are:
  • Profile source information and set characteristics
  • Determine data trends from data sets, provide accurate data models and code and develop data rules from the analysis
  • Execute big data processes such as filtering, text connotation and filtering
  • Initiate technical and pricing negotiations with data providers
  • Develop solutions for real-time distributed data processing
  • Monitor data sources and search for new Big Data predictors
  • Conduct cross-functional and design workshops for creating business goals and best work practices
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