Big Data describes the increasingly large volumes of data that companies collect every day, through social media, clickstreams, data sensors and point-of-sales. If they’re able to analyse these massive sets of structured and unstructured data and unearth the patterns and trends hidden inside, companies can discover a great deal about their customers, employees and even their business’ operational efficiency. Big Data is becoming the key basis of competition, increasing productivity and aiding innovation, as found by MGI and McKinsey’s Business Technology Office. But if we can’t get to big data, fast, is there any point?
For companies completing operations such as fraud detection and compliance reporting, for example, data needs to be analysed on demand and acted on quickly or it loses value. To get around this issue many industries, including financial services, have started to integrate outside API technology.
The Problem with Big Data
As a recent article from DataInformed stated, data has a shelf life. It’s all very well if your analytics framework can tell you how you should have kept your customers satisfied yesterday. However, you’re likely to lose out to a competitor who has worked out how to keep them satisfied today and tomorrow.
The era of big data seems to be fostering the false notion that we are obliged to retain any data that we come across as it could potentially be useful. Companies need to employ a ‘use it or lose it’ attitude in order to combat this data hoarding. Data needs to become transparent and usable at a higher frequency, making big data fast and flexible. This can lead not only to better consumer insights, but also expose variability and boost performance through the collection of accurate and detailed information on everything from product inventories and purchase behaviour to employee performance.
This is particularly relevant in the financial markets, where in banking and insurance, enterprises need immediate access to the most relevant data. They need big data, fast. It is far more valuable than the petabytes of historical data that has sat in warehouses for years. Having rapid access to relevant information can be used for low frequency forecasting, high frequency nowcasting and help management make more precise business decisions.
At iPushPull, we’re experts in delivering real-time data to the desktop for our financial markets customers, from trading services to Fortune 100 banks. Not only do we help you get access to your big data in less than a second, but we also deliver it to the applications you and your team already use, like Microsoft Excel. And we let you do more with that information by letting you share it instantly and continuously between Microsoft Excel, Slack, Symphony, the web and mobile on our encrypted, audited and monitored platform.
Next we’re partnering with big data platforms like Cloudera and SAS. Just another way we give our customers real-time access to their analytics wherever they are, whenever they need it.