How Can Data Lake Emerges as the Solution to Data Storage
A data lake is a centralized repository where enterprises can store big volumes of data in their raw form i.e. structured or unstructured and later on can be used for different types of analysis and technologies such as machine learning and big data analysis. Data is the fuel for future technologies making it immensely important to solve complex data storage and management system. It is necessary to converge the diverse data to one storage from where it is accessible to all. Currently, businesses have disconnected silos of data making it complex to share and manage. Data Lake has emerged as one solution to this problem where organizations are able to store and share data.
Benefits of Data Lake
Organizations are finding data lakes helpful for their business process because below mentioned points.
• Faster deployment of applications and services.
• Reduction in downtime
• Cost reduction in data storage and management up to 70%
• Fewer management headaches
The above mentioned are benefits based on the infrastructural level. Below benefits are outlined on the services or value basis.
• Better Customer Interaction: A data lake is capable to combine customer data from any CRM platform with social media analytics, marketing tools to churn out customers cohort based upon buying history. This analytics results in increased sales and customer loyalty as the strategies will be more target audience based.
• Enhanced R&D Innovation: With use machine learning and artificial intelligence the R&D team of organizations would be able to test their hypothesis and assumptions on the data stored in the lake which in return will enable them to make more realistic approaches and best strategies in available resources.
• Improve Operational Efficiency: Internet of Things (IoT) has enabled enterprises to collect diverse data and that too in real time. This data can be stored in Data Lake, where analytics could be run on to discover methods to reduce operational costs by before time service of machinery eliminating the scenario of unplanned downtime.
With all its benefits data lake seems to of great use but it is equally important for organizations to understand the challenges that it holds with itself. The main challenge is that the data is stored with no oversight of content. To make the data usable it is required to define a mechanism to catalog and secure data without which it is hard to even find or trust the data and result in data swamp. Data lakes require governance, semantic consistency, and access control to meet wider audience needs.
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