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4 Reasons Why Businesses Need Data Lakes

Michael Chen
Senior Manager
It's common knowledge in the modern business world that big data —that is, the large volumes of data collected for analysis by organizations—is a significant element of any strategy—operations, sales, marketing, finance, HR, and every other department rely on big data solutions to stay ahead of the competition. But how that big data is handled remains another story.

Enter the world of data lakes. Data lakes are repositories that can take in data from multiple sources. Rather than process data for immediate analysis, all received data is stored in its native format. This model allows data lakes to hold massive amounts of data while using minimal resources. Data is only processed upon being called for usage (compared to a data warehouse, which processes all incoming data). This ultimately allows data lakes to be an efficient way for storage, resource management, and data preparation.

But do you actually need a data lake, especially if your big data solution already has a data warehouse? The answer is a resounding yes. In a world where the volume of data transmitted across countless devices continues to increase, a resource-efficient means of accessing data is critical to a successful organization. In fact, here are four specific reasons why the need for a data lake is only going to get more urgent as time goes on.

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90% of data has been generated since 2016

90% of all data ever is a lot—or is it? Consider what has become available to people as Wi-Fi, smartphones, and high-speed data networks have entered everyday life over the past twenty years. In the early 2000s, streaming was limited to audio, while broadband internet was used mostly for web surfing, emailing, and downloads. In that paradigm, device data was at a minimum and the actual data consumed was mostly about interpersonal communication, especially because videos and TV hadn’t hit a level of compression that supported high-quality streaming. Towards the end of the decade, smartphones became common and Netflix had shifted its business priority to streaming.

That means between 2010 and 2020, the internet has seen the growth of smartphones (and their apps), social media, streaming services for both audio and video, streaming video game platforms, software delivered through downloads rather than physical media, and so on, all creating exponential consumption of data. As for the part that is the most relevant to business? Consider how many businesses have associated apps constantly transmitting data to and from devices, whether to control appliances, provide instructions and specifications, or quietly transmit user metrics in the background.

With 5G data networks widely starting to deploy in 2019, bandwidths and speeds are only going to get better. This means as massive—and significant—as big data has already been in the past few years, it’s only going to get bigger as technology allows the world to become even more connected. Is your data repository ready?

95% of businesses handle unstructured data

In a digital world, businesses collect data from all types of sources, and most of that is unstructured. Consider the data collected by a company that sells services and makes appointments via an app. While some of that data comes structured—that is, in predefined formats and fields such as phone numbers, dates, transaction prices, time stamps, etc.—a company like that still has to archive and store a lot of unstructured data. Unstructured data is any type of data that doesn’t contain an inherent structure or predefined model, which makes it difficult to search, sort, and analyze without further preparation.

For the example above, unstructured data comes in a wide range of formats. For a user making an appointment, any text fields filled out to make that appointment count as unstructured data. Within the company itself, emails and documents are another form of unstructured data. The posts from a company’s social media channel are also unstructured data. Any photos or videos used by employees as notes while performing services are unstructured data. Similarly, any instructional videos or podcasts created by the company as marketing assets are also unstructured.

Unstructured data is everywhere, and as more devices connect to deliver a greater range of information, it becomes clear that organizations need a way to get their proverbial arms around all of it.

4.4 GB of data are used by Americans every minute

More than 325 million people live in the US. Nearly 70% of them have smartphones. And even if you don’t count the people currently streaming media, consider what is happening on an average smartphone in a minute. It’s receiving an update on the weather. It’s checking for any new emails in the user’s inbox. It’s pushing data to social media, delivering voicemail over Wi-Fi, delivering strategic marketing notifications from apps, such as when a real estate app pushes a new housing listing. It’s sending text and images via chat apps, and downloading app/OS updates in the background.

Data is everywhere now, which means the minute that just passed while you read the above paragraph, gigabytes of data have been transmitted across the country—4.4 million GB of data every minute, according to Domo’s Data Never Sleeps report. And that’s just the United States; when combined with the rest of the world, the total volume of data grows exponentially. For businesses, collecting this kind of data is vital to all aspects of operations, from marketing to sales to communication. Thus, every organization must put a premium on safe, available, and accessible storage.

50% of businesses say that big data has changed their sales and marketing

Most people think of big data in terms of the technical aspects. Clearly, a company that works through a phone app or provides a form of streaming uses big data and is delivering a service that simply wasn’t feasible twenty years ago. However, big data is much more than delivery of streaming content. It can create significant improvements in sales and marketing—so much so that according to a McKinsey report, 50% of businesses say that big data is driving them to change their approach in these departments.

What’s the reason for this? With big data, organizations have a much more efficient path to understanding customers than in-person focus groups. Data allows for gathering a mass sample of actions from existing and potential customers. Everything from their website browsing prior to conversion to how long they engaged with certain features of a product or service are all available at high volume, which creates a large enough sample size for a reliable customer model. To be in the cutting-edge 50%, an organization needs to have the data infrastructure to receive, store, and retrieve massive amounts of structured and unstructured data for processing.

Basically, you need a data lake

The above statistics all point to one thing—your organization needs a data lake. And if you don’t get ahead of the curve now in terms of managing data, it’s clear that the world will pass you by in all areas: operations, sales, marketing, communications, and other departments. Data is simply a way of life now, enabling precise insight-driven decisions and unparalleled discovery into root causes. When combined with machine learning and artificial intelligence, this data also allows for predictive modeling for future actions.

Learn more about why data lakes are the future of big data and discover Oracle’s big data solutions—and don't forget to subscribe to the Oracle Big Data blog to get the latest posts sent to your inbox.

(Note: Corrected typo from Domo's Data Never Sleeps citation.)

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Comments ( 1 )
  • Sasah Sunday, December 22, 2019
    It's 4,416,720 GB, not 4.4 GB
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