Cloud Data Lakes to Enhance Business


Cloud Data Lake is forming a novel digital landscape. This is a cloud-hosted centralized data storage area that enables you to stock up all structured as well as unstructured data at any scale, usually using an object store, for example, Microsoft Azure Data Lake Storage (ADLS) or Amazon S3. 

The spread of the Coronavirus has boosted the transition of a data-driven era. The excessive use of the internet, the arrival of new devices and technology, the social media culture, along with the supremacy of the algorithm have had influenced literally everything including our behavior, conversations, and even lifestyle. This has resulted in the massive (that is petabytes) generation of various kinds of data. These big-data can be mined and processed to gain insights that can boost the efficiency and value of the business. Now, Cloud Data Lake enters the scene.

Conversations on the cloud, big data, and machine learning are moving towards platforms that are consistent, handy, cost-efficient, and measurable. These platforms are ready to spout into demand among various industries. Conventionally, Data warehouses have been considered as a powerful tool to store data, and even so, the cloud data lakes are the new center of attraction. This is an integrated enterprise solution that allows you to process data and generate a consumption layer in addition to the storage facility. 

Now focusing on the advantages of the Cloud Data Lakes, there are several business benefits delivered by the same. Cloud Data Lakes are experts in handling the ambiguity caused by different types of data as well as the vagueness in the availability of data. And because of this expertise, planning the investments and data strategy with targeted investments becomes more effective. The Cloud Data Lakes offers a low entry barrier and allows small to medium enterprises to test solutions in a comparatively risk-free environment. It also drives business results with the adoption of new solutions along with quick prototyping and trialing. Finally, Cloud Data Lakes address various complex business requirements by processing, transforming, and analyzing massive complex data from different sources like sensors, social media, and ERPs.

When navigating through challenges, there are a few of them to be handled. To adopt the Cloud Data Lakes flawlessly, firms need to tackle these implementation challenges. One of the challenges faced is that cloud expertise is required for design and implementation, along with domain expertise to ensure the full range of business value. Additionally, change management is also required that includes awareness, onboarding of users into the platform, etc.

The ease and simplicity delivered by many platforms are motivating quick adoption, and Cloud is the ideal platform, for now, to leverage data efficiently and to drive experimentation. Also, Cross-cloud integrations support the infrastructure and at the same time stick to the developing privacy regulations. Assessing the options cautiously and bringing together the right teams will facilitate better informed and faster decisions to survive and uphold in the rapidly growing environment.


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