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The value of the Data Lake Market is expected to reach $24,308.0 million by 2025 due to the large amount of data generated daily.
Data lakes have become a reasonable-price solution for companies who need to store a vast amount of data. Moreover, data lakes have proven to be a quick and easy way to manipulate and analyze information.
Data lakes are an essential part of every data-driven brand. To take advantage of their capabilities, brands need to understand the concept and benefits of data lakes.
What is a marketing data lake?
A marketing data lake is a cloud-based depository that provides space to store data in its raw, natural form. It collects data from multiple sources and contains information generated by customer touchpoints and cross-channel marketing activities. Data lakes also allow analytics services for marketers to help them make better campaign decisions that aren’t possible with traditional approaches.
Amazon Web Service (AWS), Cloudera Data Platform (CDP), and Google Cloud Storage (GCS) are some of the most popular cloud solutions because of their capacity to store a large amount of data.
Data lakes are an essential part of every data-driven marketing strategy that aims to provide a personalized customer experience targeting their needs. Being equipped with a large amount of information these repositories help marketers understand customer needs and take the right action on the best channel.
Difference between a data “lake“ and a data “warehouse”?
While data lakes offer more flexibility for storing unprocessed, fluid data, data warehouses have a more structured approach to information storage. Besides these main differences, data lakes and data warehouses differ in the following segments:
Data Structure
The main difference between data lakes and data warehouses is the data structure. Data lake operates cloud solutions to store structured, semi-structured, and unstructured data without limitations of size or format. By this, it provides a better insight into analytics.
On the contrary, data warehouses store processed information that is later organized in files and folders. This structure assists companies with better business insights.
Source: bmc
Purpose
A data lake defines the information’s purpose once data is stored. Whereas a data warehouse has a pre-defined purpose for all information before it’s stored. This means data lakes are less organized than their counterpart, holding all types of data, even without a specific purpose. On the other hand, data warehouses provide a comprehensive outlook on information that facilitates decision-making.
Best for
Although brands often need both types of data, it can be challenging to read raw, unprocessed data. So companies who use data lakes often hire a data scientist or utilize specialized tools for reading data. Conversely, data warehouses present data in spreadsheets, charts, tables, and other familiar forms, so it’s easy for almost everyone to read and understand the insights.
Why do we need a data lake?
Recent statistics show that the overall amount of data created and consumed will increase by 181% by 2025. Because of this, brands are facing a rising necessity for data storage that offers enough space without hurting the budget.
Besides its capacity to store a vast amount of data, data lakes provide better data management given their various features for organizing and finding data. Users can store data in separate buckets for individual channels (Facebook Ads, LinkedIn Ads, etc.) and look for individual files without typing SQL.
Moreover, this type of solution is an effective alternative if users want to keep the data in case they need it, without taking up space in data warehouses.
Data lakes are beneficial for marketing agencies that cooperate with multiple clients, as they can create an individual bucket for each client and have long-term access to attained data. Besides benefits in data management, due to its capacity to store hundreds of terabytes, data lakes are a low-cost solution that provides more value for the money invested.
Source: Forbes
How to utilize data lakes to boost your marketing strategy?
Despite the rising number of tools and technologies brands use to analyze the data when approaching new strategies, they still lack cross-channel metrics and a 360-degree customer view.
Failing to analyze the data leads to limited insights into product and service interest, the inability to personalize the interaction with customers, and failure to react in real-time to activity.
For that reason, marketers need to take different approaches and start analyzing a vast amount of data to deliver an outstanding customer experience. To do this successfully, brands need to prepare the data to make them readable to non-technical users. In this way, they pave the way to data-driven marketing strategies.
While each brand can utilize data lakes differently, these are some of the most effective marketing data lake approaches.
Utilizing flexible self-service for marketers
Equipping marketers with flexible self-service tools for handling data lakes will increasingly improve their efficiency. Self-service tools can save time spent on IT assistance and boost marketers’ performance and ability to discover data themselves.
These tools allow marketers to organize and analyze the data to deliver better insights and analytics.
Use data lakes to unite marketing, sales, and support
Recently, traditional ways of separating the function of marketing, sales, and support are starting to change. Primarily because of its tendency to create inconsistency in both B2B and B2C experience.
As data lakes promote collaborations, brands favor this solution to join teams and allow access to the same data. With this, all units can consider different views before making the final decision.
Embrace the big-data approach to marketing
The popularity of big-data approaches is rapidly increasing as it allows a better insight into market research. Analyzing the big data of all formats has become vital for understanding customers’ needs and intents. Marketers need to find a way to use the insights from big data to reach customers through various channels. They do it by constructing their strategy around email, digital advertising, content marketing, SEO, or engaging on social media. There are many testing and structured data tools out there that you should consider, to achieve better performance.
Final Thoughts
Data lakes are a powerful tool that brands can use to gain a better insight into the data they collect. With the vast amount of data, data lakes facilitate the strategical development of business. If used properly, data lakes can help brands grow and keep track of rapid changes in a data-driven world.
Author: Mitko Ivandjikov
Mitko Ivandjikov is a professional outreach specialist at Intercoolstudio, working with the team to increase their visibility and grow their customer base. He’s also an avid sports fan who spends his free time watching, reading about, or playing basketball. You can connect with him on LinkedIn.