Today, big data – that is, the large quantities of data collected for analysis by businesses – is one of the most important aspects of any strategy. From operations to sales, marketing to finance, HR, and everything in between, big data solutions keep companies at the forefront of their competition. However, how that big data is handled remains a mystery.
This is where data lake solutions come into play. A data lake is a repository where multiple sources of data can be integrated. All data is stored in its original format rather than processed for immediate analysis. Data lakes can store massive amounts of data with minimal resources using this model. The processing of data happens only when it is needed (versus a data warehouse that processes all data on arrival). Ultimately, this results in data lakes being an efficient method for storing, managing, and preparing data.
However, do you have to have a data lake if you already have a data warehouse as part of your big data solution? Yes, there is no doubt about it. When so much data is now being transmitted across so many devices, a resource-efficient manner of expressing data is imperative to a successful organization.
The following three reasons will only make data lake for enterprises more necessary as time goes on.
Since 2016, 90% of all data has been generated
It is difficult to imagine 90% of all data ever is a huge amount but is it really? Over the past twenty years, Wi-Fi, smartphones, and high-speed data networks have revolutionized the way people live. The early 2000s were dominated by audio streaming, while broadband internet was largely used for email, web browsing, and downloading. At that time, device data was at a minimum and most of the data was consumed by interpersonal communication, especially because videos and TV had not yet reached a level of compression that enabled high-quality streaming. Smartphones became common at the end of the decade, and Netflix shifted its focus from cable to streaming.
As a result, from the years 2010 to 2020, the internet witnessed the growth of smartphones (and their apps), social media, streaming audio and video services, streaming video game platforms, software delivered via download rather than physical media, and more, all of which produced exponential data usage. What’s the most relevant part to business? Consider the number of business apps that constantly transfer data back and forth between business devices, whether they are used to control appliances, display instructions and specifications, or transmit user metrics quietly in the background.
It is anticipated that speeds and bandwidths will only increase with the advent of 5G data networks. Big data is only going to get bigger, and more significant, as the world becomes ever more connected, as technology allows for more and more connections.
Business deals with 95% of unstructured data
Companies gather data from a wide range of sources in the digital age, and most of that data is unstructured. You might be surprised at the number of information companies collect when they sell services and make appointments via apps. A company like that has to archive and store a great deal of unstructured data as well, even though some of the data is structured – for example, phone numbers, dates, price listings, and timestamps. A piece of unstructured data has no inherent structure or predefined structure, making it difficult to search, sort, and analyze without additional preparation.
There is a wide variety of formats for unstructured data, as in the example above. Unstructured data can be filled out for appointments by a user by filling out text fields. Emails and documents within the company can also be considered unstructured data. Similarly, social media posts from a company are also unstructured data. When employees take notes on services they are using unstructured data, such as photos or videos. A similar problem occurs when the company produces marketing assets such as instructional videos or podcasts.
Organizations must find a way to organize unstructured data as a greater range of devices connect and deliver more information.
In 50% of businesses, big data has transformed marketing and sales
Big data is mostly thought of from a technical perspective. Big data is evidently being used by companies that operate through apps or provide a stream of services that simply weren’t possible twenty years ago. The benefits of big data extend far beyond streaming video. As a result, a McKinsey report reports that 50 percent of businesses rely on big data to change how they approach marketing and sales.
Why is this happening? Organizations can get a better understanding of customers with big data than they can with in-person focus groups. This data enables potential and existing customers to gather information on their behavior. A high volume of information is available on their website browsing prior to conversion, how long they engaged with particular features, as well as what companies offer and how well they do it. An organization needs a data infrastructure that can receive, store, and retrieve massive amounts of structured and unstructured data for processing in order to qualify for the cutting-edge 50%.
The statistics above all point to the same conclusion: your organization must have a data lake. Without data management now, the world is obvious that you’ll lose out in every area: operations, sales, marketing, communications, and more. Data is now an integral part of our daily lives, enabling precision insight-driven decisions and unparalleled understanding of root causes. Additionally, this data can be used to model future actions when combined with machine learning and artificial intelligence.
Data Lake Experts at Polestar Solutions consist of data scientists, consultants, engineers, and analysts who have helped companies streamline the data discovery, insights delivery, and administration of Data Lake platforms like Microsoft Azure, Snowflake, Hadoop, Google Cloud, and AWS. Our solutions follow security and privacy measures strictly to safeguard your data.