With the growth of data, the term used for describing the data, and the place in which it is stored has evolved. From traditional data bases, it was moved to data warehouses after which it was moved to data lakes. In addition to the size of the data, there is a wide assortment of parameters which distinguishes the concept from the predecessors. What is essentially a data lake? According to James Dixon who is CTO of Pentaho, the BI software platform, Data Lake is considered to be the storage form of data mart. If data mart is regarded as the storage of bottled water that has package, cleansed and structured water for the hassle free consumption, Data Lake is considered to be the large water body, present in the natural state. The contents of the data lake are known to be retrieved from a specific source for filling the lake. Different users of the lake come for diving in, for examining or for taking different samples. What does Data lake do? Data lake solutions plays a vital role in holding the data in the rawest form without the requirement for analysis or processing of the data. The source of the data might be non-relational or relational. As the data is known to be imported, functions present in the business firm like business analysts, developers, data scientists can catalogue, crawl, analyze or index the same without the requirement to run the same via a unique analytics system. As the data is imported, it functions by a wide assortment of applications which are inclusive of the visualization of data, processing of big data, machine learning tools, AI, to name a few. It is possible to transform this state of analytical agility to the substantial return on investment. Also Read: Data Warehousing – Traditional vs Cloud! Step by step guide Business organizations are known to go through the below mentioned stages of development for the building as well as integration of data lakes in the existing technology architecture: Stage 1 It consists of the landing zone for the raw data. Data Lake is considered to be the scalable, low cost, and pure capture environment. Data Lake is known to be built, in a separate way from the Core systems of IT. it is possible to store the data in the raw formats here. You can complement internal data at ease or with the aid of different external sources of the data. Stage 2 It involves the data science environment. Here data is used actively as a platform for different experiments. Data Lake has turned out to be the test and learn environment. Data scientists are known to analyze the unaltered data and develop different prototypes for the analytics programs. The IT firm is known to deploy adequate governance of data. Stage 3 It refers to the offload for the DWH of the business organization. In this stage, Data Lake is known to be integrated with the present enterprise data warehouse. Mass extraction and high intensity actions tend to remain in the enterprise data warehouse. However, the detailed and larger sets of data are found to be pushed to the data lake during the process. It also facilitates the hassle free storage as well as cost constraints. It is possible to make use of Data Lake for the purpose of needle in haystack searches as well as for different tasks, in which traditional indexing is not needed. Stage 4 It involves the critical component of different operations of the data. You need to keep in mind that Data Lake is considered to be an integral part of the existing infrastructure of data. Data lakes can be taken into account as a replacement of the operational data stores as well as enables the data as a service options. Businesses are capable of handling a bunch of computing intensive tasks like machine learning programs. It is possible to build application programming or data intensive applications on the top of Data Lake. The IT firm is known to deploy the stronger governance of data. Agility as well as flexibility of the data lakes is useful in dumping the data in the original format. Thus, it can turn into a sandbox in which all the developers and analysts can play. Thus, the cloud based storage can make them a specific potential security nightmare, primarily from the regulatory compliance point of view. It is necessary to apply the authentication, data encryption as well as access controls. In addition to this, it is possible to scrutinize and secure the traffic in the lake and provide backup to the data against the chances of any ransom attack. At the beginning, a separate data lake is development from the core systems of IT which serves as the pure capture, scalable and cost effective environment. It is known to serve as the thin data management layer which is present in the technology stack of the business firm which helps in the storage of raw data, before it is used in any computing environment. Thus, it is possible for the business firm to deploy the data lake with reduced impact on the already existing architecture. In the next level, the business firm might start using the data lake more actively as the platform for the purpose of experimentation. Data scientists are known to have rapid and easy access to the data. They can give more focus on conducting the experiments along with data as well as analyzing the data. In the next immediate step, which involves the offloading of data warehouses, data lakes may begin to integrate with the existing enterprise data warehouse. As the business firm retrieves the information and reach this specific stage, majority of the details which flow through the specific company, enters into the data lake. Hence, Data Lake is considered to be an integral part of the data infrastructure. It comes as the replacement of the existing operational data store or data mart and allows the provision of the data. If you’re making any drastic changes or improvements at your product or software, doesn’t it make sense to go with a company like Indium Software - Leading Data Warehouse Solution Provider. Thanks and Regards, Gracesophia
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