How to use Big Data to get a 360 view of your customers
BigData has changed a lot of things, and how people shop is one of the bigger ones. Now, customers are used to seeing personalized recommendations for products, customized event ads, and an entire bevy of buyable goods and services curated just for them. Without the massive and integrated flow of information that the best use of Big Data provides, this process would be difficult – if not impossible.
Nowadays, companies want to know more about their companies than just the information their B2C transactions give them. This holistic view of the entire personality not only helps them offer a more pertinent range of products or services to the customer, it also enables them to better stand out from the competition. So what’s the roadblock to this blissfully connected state? Often, the data needed is stored in two different places: within the company, and within third-party systems. Added to this is the challenge that many traditional data storage systems simply aren’t set up to handle this amount of information.
Big Data Rises to the Challenge
That’s where Big Data comes in. These platforms have the space and power to manage vast amounts of data with ease and speed. When combined with a cloud-based system, they’re also extraordinarily good at meeting the need of a geographically distributed and changing workforce. Merging, processing, analyzing, and generating results from a mountain of information is now very much a possibility.How much better-equipped are today’s data technologies than traditional RDBMS systems ? Have a look
That’s where Big Data comes in. These platforms have the space and power to manage vast amounts of data with ease and speed. When combined with a cloud-based system, they’re also extraordinarily good at meeting the need of a geographically distributed and changing workforce. Merging, processing, analyzing, and generating results from a mountain of information is now very much a possibility.How much better-equipped are today’s data technologies than traditional RDBMS systems ? Have a look
– Speed: Data is mined at much higher speeds
– Set Time: Systems are quicker to set up
– Volume: Terabytes of data can be processed
– Flexibility: Unstructured data can be handled
– Text-Ready: Text analytics are readily supported
– Cost Effective: Significantly greater amounts of data are processed with less budgetary impact
– Set Time: Systems are quicker to set up
– Volume: Terabytes of data can be processed
– Flexibility: Unstructured data can be handled
– Text-Ready: Text analytics are readily supported
– Cost Effective: Significantly greater amounts of data are processed with less budgetary impact