What is Data Lake in Data Analytics? Top Advantages

Innovative tools and strategies have also emerged, enabling organizations to be more competitive. Recently, the term Business Intelligence (BI) has been garnering the attention of business owners worldwide. It refers to utilizing past and present data to make better decisions for the future.

To achieve this, data needs to be first collected and then stored through a Data Lake so that it can be analyzed. In simpler words, the transformation of raw data stored in Data Lakes into relevant and insightful information. But what’s a data lake? Experts at Continuum Innovations are here to answer all your queries.

What is a 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.

Known as data analytics, the next step involves analyzing large amounts of information from data lakes to extract insights that can improve the bottom line. Using complex algorithms, it enables businesses to understand the current trends and patterns in big data.

Companies can utilize the information to make more informed decisions about allocating resources efficiently and optimizing their operations as they uncover new opportunities and navigate risks.

Fun Fact: Earlier businesses relied on another form of storage known as Data Warehouses. The model comprised extraction, transformation, and loading. So the data needed to be processed before storing. In contrast, data lakes allow extraction first, followed by loading, and finally transforming. They allow businesses to capture data from more sources, resulting in more effective analysis.

Scalability

Data lakes, like AWS, are hosted in the cloud. They provide security, scalability, and instant availability. Reliable data lake designing services providers 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. In order 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. 

Looking for Data Lake Services in Princeton?

With all the benefits that AWS offers, you can count on Continuum Innovations for data lake designing services as well as AWS data analytics services. We offer a range of cutting-edge cloud services to help improve business efficiency. These include professional cloud migration services, managed DevOps services,  Azure custom design service, AWS Connect, AWS security and compliance, AWS Media services, and AWS cloud consultancy services.

Connect with us to learn how our cloud consultants can help you with solutions that are flexible, efficient, secure, scalable, and cost-effective. We’ve helped businesses in diverse industries optimize their cloud strategy.

Ready to accelerate your business? Customized cloud consulting services are now just a call away!