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