Data Lakes are a new phenomenon in the emerging technology sector. Typically, a data lake is a big data repository where an organisation can store all of its organized and unorganized data. All the data comes in the data lake in a raw format from the source input with minimal modifications. Data Lake can be useful and serve as an advantage for data storage and processing. Data scientists can churn out the information at any given time to analyze it by using multiple tools and functions.
By adopting data lake companies can upfront manage multiple business-related critical tasks. Researchers at Aberdeen have surveyed 43% companies using data lakes and have stated that it improves their data efficiency. Moreover, its other benefits stated were that independent data is more available to all, it helps in reducing data transfer costs and also reduces the load on the mainframe.
Data warehouses which were generally used by enterprises involved high cost, whereas data lakes have advanced structure and several avenues for storing and processing of data. It is easy to manage the huge volumes of data and get better insights with less effort or calculation while being easily accessible to data scientists in swiftly solving company’s needs.
These multiple core benefits of data lakes which include; capability to open up new ways to grow analytics and make informed decisions, data migrations become easy that can be done real time and the data can be processed in different data formats. Relevant data can be stored, indexed and labelled easily which in turn can be secured properly. Machine learning becomes more effective as data engineers can implement different models to train the ML systems.
It helps in maintaining data governance in standardising the data coming from various sources and also ensures data transparency and accuracy that can be made possible by using data lakes.
Though data lakes are highly effective, it does have its downsides. Data Lakes are designed to handle raw data hence the content needs to be kept on a close check. Human intervention is of utmost necessity to ensure that the data is usable, accessible, up-to-date, and valuable. In that way, a data repository might be better suited to implementing your data initiatives, depending on the situation.
The task is how businesses can utilize data lakes and big data to gain business intelligence and revenue. Specialists in the organisation with the help of business intelligence can efficiently use advanced methodologies to work on the large data sets. It will help in procuring meaningful insights, improve business related decision making and explore new business opportunities growth and revenue maximisation.
Data lakes helps BI to access raw data, secure storage, reduced efforts at the start, and time-saving can benefit different industries. Here are a few examples.
Useful in Logistics and Supply Chain:
Cargo storage, packaging, transporting, and distribution can be helped a lot with big data. The same goes for the optimization of existing transport routes, transportation systems, delivery optimisation, and allocation of people and other resources. Big data and data lakes can help enhance operational efficiency, reduce errors, reduce delivery costs, and boost sales and revenues.
Use in Finance and Insurance
The role of big data in this industry is mainly to mitigate and combat money-related risks along with increasing productivity, and improving customer service. Data processing tools are useful in getting hidden information. This helps in faster and accurate reporting to instantly share valuable insights. Clients can receive better service due to simplified claim management and invoice processing.
Booting revenue streams in Healthcare
Big data helps professionals in the industry to promote personalized medication, vaccination assistance especially with respect to the current covid situation and reduce the costs of treatment. Better data management is utmost important for life-saving activities. Having data handy helps in the reduction of medical errors and helps improves patient safety.
Assist the Tele-communications industry
Telecom industry is highly automated and has witnessed significant changes already in that aspect. It can help boost team productivity by taking care of mundane tasks that involve customer relationship management and help to reduce operational expenses and improve service delivery. Lastly, companies can innovate and introduce new products as well.
Along with this Data Lakes and Big Data is something that is benefitting companies by and large by reducing costs and improving operational efficiency. Companies and Enterprises can gain huge monetary benefits and maximise revenue by effectively utilizing these resources.