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BIG Data Analytics

Identify the valuable insights from data

"Why is BIG data analytics important?"

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers.

Source: Forbes

How Is Big Data Analytics Using Machine Learning?

Makes Sense Of Big Data

Big data refers to large sets of structured and unstructured data that cannot be handled with traditional methods. Big data analytics can make sense of the data by uncovering trends and patterns. Machine learning can accelerate this process with the help of decision-making algorithms. It can categorize the incoming data, recognize patterns and translate the data into insights helpful for business operations.

Compatible With All Elements Of Big Data

Machine learning algorithms are useful for collecting, analyzing and integrating data for large organizations. They can be implemented in all elements of big data operation, including data labeling and segmentation, data analytics and scenario simulation.

Carrying out market segmentation

Enterprises need to carry out market research that can delve deep into the minds of potential customers to facilitate insightful data. Machine learning's supervised and unsupervised algorithms to interpret consumer patterns and behaviors accurately. Media and the entertainment industry use machine learning to understand the likes and dislikes of their audiences and target the right content to them.

Exploring customer behavior

Machine learning then helps businesses explore audience behavior and create a solid framework of their customers. This system of machine learning, known as user modeling, that mines data to capture the mind of the user and enable business enterprises to make intelligent decisions. Facebook, Google, etc. rely on user modeling systems to know their users inside out and make relevant suggestions.

Personalizing recommendations

Businesses need to offer personalization to their customers. Be it a smartphone or a web series, companies need to establish a strong connection with their users to deliver what's relevant to them. Big data machine learning is best put to use in a recommendation engine. It combines context with user behavior predictions to influence user experience based on their activities online. This way, it can empower businesses to make correct suggestions that customers find interesting. Netflix uses machine learning-based recommender systems to suggest the right content to its viewers.

Predicting trends

Machine learning algorithms use big data to learn future trends and forecast them to businesses. With the help of interconnected computers, a machine learning network can constantly learn new things on its own and improve its analytical skills every day. In this way, it not just calculates data but behaves like an intelligent system that uses past experiences to shape the future. An air conditioner brand can depend on machine learning to predict the demand for air conditioners in the next season and plan its production accordingly.

Aiding decision-making

Machine learning uses a technique called time series analysis that is capable of analyzing an array of data together. It is a great tool for aggregating and analyzing data and makes it easier for managers to make decisions for the future. Businesses, especially retailers, can use this ML-boosted method to predict the future with commendable accuracy.

Decoding patterns

Machine learning can be highly efficient to decipher data in industries where understanding consumer patterns can lead to major breakthroughs. For example, sectors like healthcare and pharmaceuticals have to deal with a lot of data. Machine learning can help them analyze the data to identify diseases in the initial stage among patients. Machine learning can also allow hospitals to manage patient services better by analyzing past health reports, pathological reports and disease histories. All of these can lead to better diagnoses at healthcare centers and boost medical research in the long run.

BACHcode uses Big Data

to AI Health-Check a Person:

Our Approaches:

Big Health Data

AI Health Check algorithms by analysed around 50,000 people health profiles

Data Mining and Modeling

With the algorithms, end-user input their (1) anthropometric (weight, height, age, etc) and (2) habitual data (hours of sleep, exercise, water drink, alcohol), then a AI Health Check report will be provided instantly.

Customer Benefits

Health Check results: user bio-data such as blood pressure, fasting blood glucose, cholesterol level, triglycerides, etc. And Long term chronic risk summary.

Insurer Benefits

Insurers can understand health risk of end-users and enrich the end-user profiles, which can further works with the recommendation system to recommend a suitable insurance product

Analysing the Relationship between

Bio Data (Blood Pressure, Blood Glucose, Cholesterol, etc.) and Health Factors(Anthropometrics, Physical Activities, Lifestyle, Medical History)

BACHcode Big Data Analystics - AI Health Check

Source: ReHealthier

Recent Work

Projects that ride on BACHcode Big Data Analystics

Re-insurance Company

Health modeling supports their underwriting

BACHcode's big health data anlystics machine learning models are used by re-insurance company to judge the health risk of medical insured clients

Eat Rite by ReHealthier

Instant AI Health Check and estimation of chronic risk

BACHcode award-winning mobile app has equipped with AI Health Check for client to understand their health risk any time and to start their healthy lifestyle today!

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