They say big data is a powerful tool to get insights about your business and make the right decisions but do you know what big data analytics in business really means? If you want to know more about it and how you can analyze it to tailor meaningful strategies, you are in the right place. Read to know the right big data analytics meaning, examples, and how you can benefit from it.
Big Data Analytics Meaning for Beginners
Although the term big data analytics was coined way back, it has gained high popularity in the past two decades. Big data is a concept of collecting information related to a business – its customers, strategies, market trends, etc. Hence, big data analytics in business refers to examining this data and fetching useful information out of it to make informed decisions.
Analyzing big data helps organizations operate their businesses better and accelerate their growth in the way they aspire. Since big data is not useful enough in its raw form, it usually involves studying statistical algorithms, behaviors, etc.
Real-Life Big Data Analytics Examples
Now if you want to know some easily understandable big data analytics examples, here are a few relatable ones:
Based on your browsing history, wishlist, age, gender, geographical location, etc., Amazon discovers your shopping habits and predicts the kind of products you are interested in. Hence, your app dashboard shows more products from the category you are more interested in. Analyzing large data based on age groups, ethnicity, etc. further helps the brand come up with newer features.
Similarly, Facebook’s database collects hundreds of terabytes of data in the form of messages, media, etc. every day. It structures that data to show relevant content recommendations and ads to every individual user.
You can find endless examples of how big data analytics in the business help the company make safe decisions. Big data is stored in complex, large amounts and helps to do personalized marketing for the target audience. Furthermore, this analysis helps brands manage risks and carry on an efficient business model.
How You Can Analyze Big Data to Amp Up Your Business
In this data-driven world, there are many ways to collect data and use it to outrank your competition and derive the right strategies for your business. If you want to enhance your business value through insights gained from your data, here are the most successful techniques that really work.
1. Collect, Process & Clean
Once the data is collected, you must process it properly and only keep the information you require. You must delete irrelevant or duplicate data to avoid wasting time and money.
2. Data Mining & Dividing the Audience
Look out for the current trends and the leading behavioral patterns based on the text and media collected. Identify the anomalies and cluster the data accordingly.
3. Make Predictions & Manage Risks
Based on the processed data sets, predict what features or products would be loved by your audience in the times to come. Identify the risks that may follow, curate the required risk management strategies, and work on creating opportunities.
4. Use Artificial Intelligence & Machine Learning
Using artificial intelligence and machine learning will help you gain deeper insights into your audience and find the current patterns from complex data.
5. Customize Your Approach
Since personalization is the key to bringing more engagement from your customers and generating more leads, it is not possible if you have a large audience. Hence, divide your audience into segments based on various criteria and approach them with your customized message via email marketing or other successful strategies. Engaging with your audience in a more customized way affects their browsing and purchasing behavior.
The Bottom Line
We hope we helped you understand what big data analytics is in business and how you can use it correctly to curate the best solutions for your company. From education to transportation, weather forecasting, healthcare, entertainment, and even the government sector, big data has become a crucial part of the marketing game. If you understand the data you’ve collected, you can gain countless benefits no matter what your domain is.
Various frameworks and tools can help you collect and analyze big data. Some of these are Hadoop, MapReduce, YARN, NoSQL databases, Spark, Tableau, etc. You can use these tools collectively to govern big data and provide maximum benefits to your business. However, with growing privacy concerns among users, collecting quality data and keeping it secure is a huge challenge.