How to Leverage Big Data & Machine Learning for Business Insights

Big Data & Machine Learning helps businesses a lot and that is why these two topics are usually discussed in the companies. The companies need handy insights from the data that they have generated and for that companies like machine learning algorithms for big data analytics. So, let us start with the basics and get to know about these hot trends and how it can be beneficial for your company.

What is Big Data?

Well if we define big data then it is the significant amount of information gathered, analyzed and implemented into the business. That Big data concept emerged as a culmination of the data science developments of the past 60 years. It basically tells which data is useful for business and which days isn’t. There are two ways to find it: 

A. Data Submitted: The data which is submitted, for instance when the user creates an account on the website, subscribes to an email newsletter, or performs payments etc. 

B. Data is a result of other activities: Web behavior in general & interact with ad content in particular.

Data Mining along with data analytics are main ingredients of big data solutions. In particular data mining stands for collecting data from different sources, and data analytics is making sense of it. These sorted and analyzed data can uncover hidden patterns and insights for every industry which makes your business process seamless and easy. It is difficult to make sense of this collected data and it takes more than to set up a Data Management Platform and program a couple of other filters to make this information relevant. And at this point Machine Learning comes into account. 

What is Machine Learning(ML)?

Machine Learning processes the data by decision-making algorithms to improve operations. Machine Learning algorithms get this incoming data and recognize patterns into insights for business operations. ML algorithms are also used for decision making process for automation process.

What is Machine Learning in Big Data?

ML algorithms are very much useful for data collection, integration and analysis. ML are a must for large organizations that generate tons of data as it can be applied to every element for Big data operation that includes:

1.Data Labeling & Data Segmentation

2.Data Analytics

3.Scenario Simulation

Machine Learning & Big Data Use Case

Let us have a look at how businesses combine both technologies and help the businesses in succeeding in the market. 

Market Research & Target Audience Segmentation

If you know your audience then you are close being a successful business. But for a market & audience research, you need more than surface observations. At this point Machine Learning algorithms study the market and help you know your target audience and what their behaviour towards your business is. With a combination of supervised and unsupervised machine learning algorithms you can find out: 

1.Patterns of your user’s behaviour

2.User’s preference

3.A Portrait of your target audience

This technique is widely used in Advertising, Media & Entertainment, eCommerce and other industries.

User Modeling

User Modeling is used for the continuation & Elaboration on Target Audience Segmentation . This method understands the user behaviour and forms a detailed information of a particular segment. With ML for big data analytics, you can predict your user’s behaviour of users and make your business successful with intelligent decisions.

Facebook uses user modelling and has one of the modest systems that constructs a detailed portrait of the user and suggests the new contacts, pages, ads, communities and other content. 

Recommendation Engines

You have seen that search engines and online OTD platforms like Amazon & Netflix show relevant suggestions all the time. That is because of the recommender systems. A recommendation engine is one of the best Big data Machine Learning examples and how much these services can make life easier. These suggestions engines are always on point and show the intelligence of Machine Learning in Big Data.

Predictive Analytics

If you want to succeed in your business then you need to know & understand your customers. The predictive analysis in action allows calculating the probabilities of various outcomes & decisions with a small margin of error. It is usually productive for

1.Suggesting Products on eCommerce Platforms

2.Providing information on fraudulent activity in ad tech projects

3.Calculating the probabilities of treatment efficiency for specific patients in healthcare

Ad Fraud, eCommerce Fraud

Ad Fraud is a very big problem of the Ad Tech industry and it claims 20-30% of user’s data and money in advertising. Machine Learning algorithms help to fight by:

1.Recognizing the patterns in Big Data

2.Assessing their Credibility(whether they are bots or not)

3.Blocking them out of the system before any damages are done

Chatbots

Chatbots are also known as conversational user interface and in most of the cases consist of Big Data & Machine Learning algorithms. It can easily adapt to a particular customer’s preferences after many interactions. Some well-known chatbots are Amazon’s Alexa and Apple’s Siri

With all the above points we know that big data is an amazing technology with the potential to uncover hidden patterns for more effective solutions. If you have big business that need big solutions from day to day operations then ML helps you find ways with minimum human supervision and interaction. From analyzing & predicting user behaviours to learning their preferences, you can have everything for your business.

Read More: VerveLogic

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