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General Published on: Tue Apr 15 2025
Large enterprises and companies have to deal with a large velocity, variety, and volume of data. As it keeps growing exponentially, more enterprises have started adopting data lakes. It provides companies with the ability to get a competitive edge with advanced capabilities like machine learning, analytics, and real-time insight. As a data lake is a centralized repository that becomes beneficial for businesses to store raw and structured data at any scale, it becomes easier for them to store and use data. However, certain data lake challenges always prevail, which requires proper knowledge.
Data Lake can become a major challenge without a proper implementation strategy. If there is no proper strategy made by enterprise data lake consulting services, it can become unusable, unstructured, and more like a liability than an asset. From cost overruns to poor governance, and data silos, there are a lot of data lake challenges that prevail. Hence, enterprise data lake consulting services tend to become an ideal choice as they have the tools and expertise and provide strategy guidance to transform data lake into a usable and scalable reality.
So, here, we will learn about some of the most common data lake challenges associated with implementation strategy and also understand how enterprise data lake consulting services can help overcome them.
The primary goal of the data lake is to break down data silos and create a unified source of truth. However, even though it’s the main purpose, there are several organizations that face data lake challenges. It is true that a business will have several departments, and they might upload data in incompatible formats that do not have standardized or metadata tracking. This will lead to a fragmented database within the lake.
They can create the right approach for this issue with enterprise data lake consulting services. They can initially conduct a comprehensive data audit throughout the organization. This will help to establish standard data in the pipeline and implement a metadata management framework. This will make sure that the data from different sources remains harmonized. Consultants can also provide training and guidance for enterprises to select tools for cataloging and schema-on-read, which are crucial for unifying disparate data sets.
Several enterprises clearly jump into data lake implementation without having a clear roadmap. It is important for businesses to understand that it requires a proper implementation strategy and a clear roadmap. When there is no clarity on success metrics, use cases, or an architectural decision, it will only lead to delayed rollouts and mounting costs.
Leveraging the knowledge of enterprise data like consulting services is important to find a proper implementation strategy based on your business requirements. It includes proper assessment of business objectives, defining use cases like fraud detection, IoT, data, integration, or customer analytics, and designing a scalable architecture. The consultants are knowledgeable in providing a clear roadmap with measurable milestones to ensure that every step of the implementation is aligned with the ultimate business goals.
Also Read: Data Lake Architecture: Design Principles and Best Practices
A data lake is a central repository that might store a mix of insensitive and sensitive data that comes from multiple sources. If organizations do not apply proper governance and security measures, there are chances of data breaches, misuse, and regulatory non-compliance. Moreover, without any proper data ownership or access control, businesses will be unable to handle the chaos.
With enterprise data lake consulting services, businesses will be able to implement a data governance framework. These are customized according to the enterprise's requirements. The consultants not only provide proper implementation strategy, but they also handle role-based access controls, audit trails, data lineage, tracking and encryption protocols. The consultants are well aware of the requirements of security measures and ensure compliance with major industrial regulations like CCPA, HIPAA, and GDPR. Integration of governance into the foundation makes sure to eliminate data compliance risk and ensure transparency.
There is no denying the fact that data late promised to be a cost-effective choice that ensures capability, especially when it is hosted on cloud platforms. However, one of the most common data lake challenges is poor architectural choices and uncontrolled data ingestion. These results in increasing cloud storage and compute costs. If companies are not able to make proper cost monitoring, they will end up increasing budgets and limited return on investment.
Experienced consultants offering enterprise data lake consulting services can conduct a proper cost optimization assessment. This is a part of their implementation strategy. They guide organizations to choose the right mix of cloud services, depending on their data volumes currently and in the future. With their help, businesses can also establish life-cycle policies that optimize costs without compromising on accessibility. Automated alerts and monitoring can be beneficial to help maintain a scalable and cost-effective infrastructure.
Enterprises mostly have their own data systems, mainframes, or ERP platforms that they have been using for a long time. It might not natively integrate with modern data lakes. Therefore, synchronizing and migration of data from their legacy system can become technically complex to handle and resource intensive.
With enterprise data lake consulting services, businesses will be able to build custom connectors, API integration, and ETL pipelines. This will bridge their legacy systems with the latest infrastructure. The employment of hybrid architecture and data visualization techniques can be beneficial to get real-time access without complete migration. It is a part of the implementation strategy as the approach minimizes disruption and maximizes value.
With the growing data lake, getting information in real-time of vast data can become a performance issue. Poor partitioning, inefficient query execution, and lack of indexing are some of the most common reasons to face data lake challenges and can severely hamper the analytics.
Enterprise data lake consulting services leverage techniques like indexing data, partitioning, and pre-compute views, which accelerate query execution. Most of the consultants would recommend implementing query engines like Amazon Athena, Apache Presto or Dremio as per the workload. Additionally, their implementation strategy includes parallel processing and distributed computing framework to handle the huge data set easily.
When it is about creating and managing data lakes, it involves extensive skills in different niches like security, cloud, architecture, governance, data engineering, and a lot more. Companies and their internal team might not have complete knowledge of different aspects, which can result in disrupting the implementation strategy and lead to sub-optimal decisions and delays.
Working with enterprise data lake consulting services can fill the gap as you get access to a cross-functional team of experts. They ensure efficiency and fast solutions. They have extensive knowledge of managing end-to-end implementation, creating proper implementation strategies, and providing teams with specialized resources. This can accelerate deployment and enable knowledge transfer for the in-house team.
Also Read: How Enterprise Data Lake Consulting Services Transform Raw Data into Business Gold?
Implementing a data lake is definitely not a small thing. While data promises to be scalable, unified, and intelligent storage, it requires a proper implementation strategy with technical, organizational, and financial knowledge. There can be several issues, from cost overruns and data silos to skill shortages and governance gaps, that the enterprise requires navigating to ensure success.
Enterprise data lake consulting services provided by Hexaview Technologies can be a great decision. Here, you get strategies and professionals with different expertise. The well-defined implementation strategy, hands-on support and deep domain expertise of consultants become beneficial for organizations to build the right data lake that is powerful and future-ready.
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