What are the top data link challenges?
How can I avoid the top data lake challenges?
What are the critical components of Data Lakes?
If these questions bother your mind too, then this article is for you! In this article, we will be discussing the various components and the challenges of Data lakes and how you can help tackle each of these easily. So without further ado, let us get into it!
Data Lakes have been popular for the last ten years, and still to stay in trend as they diss the traditional approach to data management methods that include data warehouses and databases. They have numerous advantages they can help deal with a large amount of data, they are highly scalable, and they can store various kinds of information rather than being stagnant to one selective data.
Though they might seem picture-perfect to read about, they do have certain challenges that app development companies need to tackle. These challenges can limit the workflow and cause delays in delivery of the product. But does this mean that Data Lakes are worthless? No! These can be resolved if handled properly. Before jumping to conclusions let us begin by understanding what data lakes are.
Understanding Data Lakes
Before proceeding further it is essential to understand what data lakes are. This is commonly known among people who deal with database management and sorting and searching of data records. It is the source of data that is used by app developers and processors in the raw format. They can have different sizes depending upon where they are being used and for what purpose. They have adaptable sizes and can be increased according to the need of the user. This is the reason it is the choice of mobile app development companies and is highly recommended by app developers.
Why choose Data Lakes?
There are several reasons why top app development companies prefer using data lakes. The most important is that they are highly adaptable and scalable according to the task at hand. They are systematic collections of data that can be stored in various formats. They have also been proven to be extremely important for analyzing how a product might perform in the future by performing algorithm analysis. The reasons for choosing data lakes are as follows:
1. It helps in organizing the entire data of the company in a single cloud space
2. It increases the efficiency of the task
3. It helps to conduct easy transactions without worrying about additional APIs being used in this process
4. They are highly flexible
5. It helps reduce the errors in the system
6. Helps reduce data redundancy
7. Avoids loss of data due to unfavorable circumstances
8. It makes searching for data easier.
Data Lake Architecture
After looking at the advantages of using a Data Lake, it is time to take a look at its architecture of it to gain a clear perspective of considering investing in one for your own app development company. It consists of the following main components. The list is as follows:
2. Curated and Sorted data
3. Raw unstructured data
4. Analysis Sandbox
5. Archive for storing the sorted data
The architecture must follow the following guidelines to avoid any errors in the system. It is as follows:
1. Keep a constant check for data being sent overseas for processing
2. Security is essential while handling data
3. The reloads and intervals are known as the metadata
4. One single party can have multiple admins to reduce the workload in the company.
5. It is the primary job of the admins to monitor and ensures that control is maintained on the ELT process to avoid loss of data
Data Lake Challenges
There is serval reason why this approach to the maintenance of data is not working for you. It is as follows:
1. Not cost-effective
Every company has its own set budget for the management of its data and chances are that because of being over budget, this system might not be working for your betterment and profit. This system needs a particular amount of time to merge with the workflow and requires time-to-time maintenance. It is easier to deploy a Data Lake than to manage it. This step can consume a lot of money for the company.
2. Difficulty in Management
Another reason why this might not be working out for you is that you are facing a lot of issues with managing this data lake. This can be due to improper staff or lack of organization of data within the data lake. It is the duty of the user to ensure that there is no redundant data being stored within the system. Once the complexity of the system increase there are also security threats that come into account. Hence having essential security measures is crucial to avoid leaking sensitive information to the app development company.
3. Long investment period
As mentioned earlier, this system takes a long time to settle in your workspace. Impatience can lead to a loss for the company. Once you set up the data lake, seeing the returns associated can take time. It is important that you keep faith in this system and continue to use it instead of leaving the whole process in hand. It is also necessary that you have the right security, data management, and analytical tool and help to deliver the correct amount of workflow in order to gain the maximum benefits from this method of handling data.
It is crucial for any app development company to know the benefits, components, and challenges that come when they choose to use data lakes for the management of their data. Data lakes
need a specific amount of time to mature in order to see the maximum profit returns. But, they are highly scalable and flexible and help avoid data errors in the system. This is the reason they are favored in the IT sector for managing larger chunks of data. Before investing in this, it is important that you set your goals and budget clearly to avoid losses related to it.