Big data is a term that refers to the huge volume of data – both structured and unstructured – that inundates a business on daily basis. However, it’s not the amount of data that’s necessary. It’s what organizations do with the information that matters. Big data can be analyzed for insights that result in better decisions and strategic business moves.
Who uses big data?
Now let’s discuss a number of the benefits of real-time big data analytics.
1. Quickly recognize errors — Suppose an error has occurred and needs to be resolved ASAP. With real-time big data analytics, this error is recognized promptly and quickly remedied.
2. Savings — Even, however, the implementation of real-time big data analytics can be costly, the high value of immediate data analysis can make up for this expenditure.
3. Progressive services — Monitoring items and services through big data analytics may lead to higher conversion rates for customers, which successively may lead on to higher profits.
4. Real-time fraud detection — The team managing the safety of the systems and servers can be rapidly and effectively informed of fraud, allowing them to take measures in real time, as soon as the fraud is identified.
5. Strategies toward competitors — Big data analytics helps in providing an exact detail of competitors, such as launching a brand new item, decreasing/increasing prices for a specific time or focusing on users from a specific location.
6. Insight — Sales insights are very important for knowing wherever sales stand. These insights could lead on to extra revenue, like not losing a client within the long run, checking the bounce rate and finding the best ways of expanding sales by analyzing real-time big data analytics.
7. Trends — Decisions by analyzing customer trends can be possible with real-time big data analytics.
Now let’s have a look at the cons.
1. Tools not compatible — The most widely used tool for big data analytics is not currently able to handle real-time data. Therefore we have many expectations with Hadoop that in future Hadoop will add functionality for a real-time approach.
2. New approach required — With the constant inflow of real-time big data, a completely different approach is required. This could be a challenge for some organizations and could lead to alteration of some decisions and plans.
3. Possible failure — Some organizations may see real-time big data analytics as a shiny new toy, and need to execute it promptly. However, if not implemented properly, this might cause a large number of issues.
The Big Data trend is sweeping across each business – and firms everywhere are keen to learn more about this topic so they can better understand how it can improve their business in long run.
In the end, when weighing big data pros and cons, most organizations decide that the upsides outweigh the downsides. However, the relative drawbacks and advantages of big data are always worth careful consideration before moving for a new big data project.