A new era for data: What’s possible with as-a-service

But the right amount of data, clean and properly channeled, can quench a business’s thirst for insight, power its growth and lead it to success, says Matt Baker, senior vice president of corporate strategy at Dell Technologies. Like water, data is neither good nor bad. The question is whether it is useful for the purpose at hand. “It’s difficult to get data in a general format, in a holistic way, to align it properly,” says Baker. “In order to get good results, it has to be refined and organized in some way to make it useful, safe and reliable.”

According to a recent study of more than 4,000 decision makers conducted by Forrester Consulting on behalf of Dell Technologies, many organizations are overwhelmed by the data. ્યારેSometimes double or even triple — and 75% say the demand for data in their organizations has also increased.

Research firm IDC estimates that the world generated 64.2 zetabytes of data in 2020, and that number is growing at a rate of 23% per year. Zetabyte is a trillion gigabytes-to put it in perspective, it’s enough storage for 60 billion video games or 7.5 trillion MP3 songs.

Forrester studies show that 70% of business leaders are collecting data faster than they can effectively analyze and use it. Although executives have plenty of data, they have no means of gaining insight or value from it જેને what Baker calls the “ancient mariner” paradox, after Samuel Taylor Coleridge’s famous epic line, “water, water everywhere and not a drop to drink.”

Data streams turn to data flood

It is easy to see why the amount and complexity of data is increasing so fast. Each app, gadget and digital transaction generates a data stream and those streams flow together so that more data streams are generated. Baker offers potential future scenarios in brick-and-mortar retailing. The loyalty app on the customer’s phone tracks her visit to the electronics store. The app uses a camera or Bluetooth proximity sensor to sense where it is and predicts what the retailer might buy by tapping information about the customer’s demographic and past purchase behavior. When it passes through a particular wing, the application generates a special offer on the ink cartridge for the customer’s printer or an upgraded controller for its game box. It notes that sales results, remember for the next time, and add complete interaction to the retailer’s ever-increasing sales and promotion data, which can then entice other shoppers with smart targets.

Adding to the complexity is the often disliked set of inheritance data. Most organizations do not have the luxury of creating data systems from scratch. They may have years of accumulated data that must be cleared to be “drinkable,” says Baker. Even something as simple as a customer’s date of birth can be stored in half a dozen different and inconsistent formats. Multiply and get clean, useful data suddenly seems impossible.

But abandoning old data means abandoning potentially invaluable insights, Baker says. For example, for a company trying to build a more efficient supply chain, historical data on warehouse stocking levels and customer ordering patterns may be key. Advanced Extract, Conversion, Load Capabilities – are essential tools designed to streamline and streamline various data sources.

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This content was created by Insights, the custom content arm of MIT Technology Review. It was not written by the editorial staff of MIT Technology Review.

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