Top Benefits of Using Data Lake
Data Lake is now a lot more than a tool—it’s a strategy. Any amount of data that comes from various sources is stored in its digital form in a flat architecture. Each element of the data is assigned a set of labels and an identifier so that relevant data is used for analysis or transformation processes whenever a query is made.
Benefits of Data Lake
Scalability
Data lakes, like AWS, are hosted in the cloud. They provide security, scalability, and instant availability. Cloud Managed Service Provider can scale the amount of data that requires storage. This increases profitability because you only need to pay for what you consume. Since any and all data is stored in one place, the cost of pulling it for analytics is low.
Multi-structured data can be stored from diverse sources in data lakes. It can store XML, binary, sensor data, logs, chats, social data, and people’s data. The AWS data lake offers schema flexibility and supports many languages beyond SQL for advanced analytics.
Improved Client Interactions
AWS data lake allows businesses to combine the customer data hosted on the CRM with data analysis from purchase histories, social networks, incident reports, and other sources. It helps understand clients better with insights into tailored strategies dedicated to providing them with better care.
Democratized Data
Data lakes enable centralized data storage, which means all data is accessible to everyone in the organization. Democratization makes necessary data available to everyone, from the top executives to the middle management and others, to help them make sense of things before making viable and timely decisions at their level.
In addition, centralization helps eliminate data silos, i.e., multiple security policies, data duplication, and difficulty with collaboration. The data is safely cataloged, indexed, and offers downstream users a unified space to look for all data sources.
Improved Customer Relationship
In order to help the company, identify the most profitable customer cohort, the reason for customer churn, and the promotions or rewards that will boost loyalty, a data lake can combine customer data from a CRM platform with social media analytics, a marketing platform that includes buying history, and incident tickets.
Boost R&D innovation options
Your R&D teams can use a data lake to test hypotheses, clarify assumptions, and evaluate the results. For example, choosing the right materials for product design can result in faster performance, conducting genomic research can result in more effective medications, and understanding customer willingness to pay for various attributes can help your teams better understand how to price their products.
Boost operational effectiveness
With real-time data coming from internet-connected devices, the Internet of Things (IoT) introduces more methods for gathering data on operations like manufacturing. To find ways to save operational costs and improve quality, it is simple to store and run analytics on IoT data provided by machines.
Insightful Resource
Unlike data warehouse ETL, a data lake does not filter out any information. In fact, every piece of data directly goes into the lake from the source. This makes data lakes a very resourceful, insightful, and rich pool of information.
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