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3 Best Strategies to get the most out of Data Lake Solutions

Data lakes have proved to be of immense benefits for the business and thus its popularity has enhanced manifolds in the past few years. However, you need to move past any sort of unrealistic expectations and over hyped promised to find the actual value of the data lakes. Prior to jumping to implementation, you need to remember that it takes immense thoughts and planning to develop a data lake. Data lakes offer immense flexibility and power at the reduced cut off from the pocket. You need to choose the perfect combination of the technologies to ensure that they will work perfectly now as well as in future.

Here is a list of few of the strategies which help in getting the most out of the data lake solutions:

Understanding the bigger picture after the creation of Data Lake

You need to opt for a data analytics strategy for mapping the goals, principles, integration approaches, implementation strategies as well as technology road map of the business organization. In case you do not possess either of those, it might become an issue. You require understanding what you are trying to achieve, before figuring how to reach the phase.

A data lake contributes to being an integral part of the complete ecosystem of the source systems, ingestion of pipelines, integration as well as data processing technologies, meta data, database, data access layers as well as analytics engines. The data analytics strategy, you are planning to adopt should be capable of providing answers to questions, related to every component, in a detailed way.

The capability model is considered to be one such approach. As you have received the capability model, you should ensure to adopt it. You can begin by figuring out the relevant parts. You do not require any sort of real time image or ingestion data. You need to bid goodbye to those specific species. Machine learning might be a great idea but at this stage, you are definitely not ready for it. You can keep it but do not forget to label the same for exploring it in future.

The ultimate goal of a capability model is the initiation of conversations, regarding what the system should be doing now and what are the services which are essential for accomplishing the specific objectives and how it is possible to fit the parts together. As you have gained success in sorting the data and analytics strategy, you are going to find the road to success.

Also Read: Data Warehousing – Traditional vs Cloud!

Choosing the right technology, catering to the needs of the business

Speaking of the capability model, as you have figured out different parts of your data ecosystem, you can conduct a research on the best of breed technologies. You need to plug it and you can be ensured that it is going to function in a proper manner. You need to have answers to specific questions such as whether the technologies will function with one another, whether they will be functioning with the already existing IT systems, whether the technology will accomplish the requirements of your business in the near future and present and who will develop the data lake and integrate the same with the data ecosystem of larger size.

Finding answers to these questions are essential. In case the people, present in your IT group has the right experience, skills, and bandwidth, it is recommended to seek their assistance. Else, you should seek assistance outside. In case you have selected the end to end solution, you can refer to the partner program of the vendor. In case you have made up your mind to combine the solution of your own from the right blending of commercial and open source products, it might be a challenge. Hence, you should search for advisors who have an ample experience along with a wide assortment of integrations and technologies.

Whether you are planning to do it alone or you intend to hire someone, selecting technology is considered to be an integral part of planning the data lake. As the tech stack gets nailed down and the architecture has been finalized, you should start the development process at a faster rate.

Developing an ongoing support plan

As you come up with a plan for the development of Data lake solutions, you should keep the management and maintenance in mind. You need to focus on certain aspects such as who is going to turn the lights on, who will take the responsibility for ensuring that the pipelines which are feeding the data will get junked up with the malformed or corrupted source data, in what ways you are going to handle crucial governance issues such as access to control as well as operations, security, etc.

Cloud native data as well as different analytics platform are developed from the group up for reliability and redundancy. Hence, you can also reduce the downtime virtually. A data lake, which is developed on those specific technologies are capable of offering trouble free operations for your application requirements.

A certain thing that you need to remember about the data ecosystem is that it is comprised of a wide array of moving parts such as data engine, storage, pipelines, and access layer component. You should ensure to cover all your support needs.

In the past, business firms used to rely on data warehouses for the storage, processing, and management of collected data. As big data is pushed into the systems, and storage costs are raised, few business entities start the movement of data into the latest kind of repository, referred to as Data Lake.

A data lake has a wide array of benefits in comparison to different kinds of data repositories like data marts or data warehouses in part owing to its capabilities for the storage of different kinds of data such as external, internal, unstructured or structured.

Apart from the structural advantages, the data lake brings an improvement in the data democratization as well as accessibility. Though the data scientists are recognized to be the prime users of the data lakes, the presence of repositories is useful in the extraction of insights from the enterprise data faster, effectively and efficiently. 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 Lake Solution Provider.

Thanks and Regards,

Gracesophia