Despite their benefits, organizations do face challenges with data lakes. Gartner analyst Donald Fienberg highlights why data lakes fail in, “How to Avoid Data Lake Failures.”
Some of the common challenges with data lakes include:
- High implementation costs
- Presence of Data silos
- Lack of technical skills
If not implemented well, data lakes can hamper rather than enable analytics success.
How does working with a Data Lake managed services partner (MSP) like Ellicium help enterprises? Let’s discuss the benefits.
5 reasons to work with a Data Lake MSP
Companies must consider the following reasons to work with a data lake managed services partner:
1. Lower costs
Data lakes are expensive to implement and maintain over time. Though cloud platforms and technologies like Apache Hadoop are free and open-source, companies can spend months setting up a data infrastructure. This can add to the overall business costs.
As data volumes and complexity keeps growing, in-house data lake infrastructure is expensive to upgrade and maintain. Organizations also incur the costs of employing and retaining in-house data specialists and professionals.
By using inherent data systems and technical resources, MSPs can lower the costs for companies looking to implement data lakes.
2. Technology issues
Outdated in-house technologies and infrastructure understanding restrict companies in their data lake implementation. Existing data lakes require constant data flow and transformation for data analytics. Additionally, most data lakes use the popular Hadoop framework. While a Hadoop-based data lake works for large datasets, it is not ideal for smaller datasets.
On the other hand, data lakes MSPs work with modern and innovative Big Data technologies like Cloudera and Snowflake. While Hadoop works as a repository for raw data, Snowflake supports capabilities like real-time data ingestion and JSON.
3. Skills shortage
The industry demand for skilled data professionals like data scientists and engineers continues to increase every year. 60% of companies find it challenging to hire qualified data scientists due to a severe talent shortage.
Due to a severe talent crunch, companies often don’t have the technology bandwidth to transform their data into useful analytics for better decision-making. Besides that, organizations must develop a “data-centric” work culture to attract and retain good talent. As data technologies continue to change, organizations need to spend time and money “upskilling” existing resources.
MSPs have an available team of experienced data specialists, who can get started with implementing data lakes in a short time.
4. Poor data quality
According to Gartner, poor data quality costs companies almost $15 million every year. Data-driven organizations are dependent on high-quality data to drive the best results. Organizations face multiple data-related issues including incomplete data, hidden data, and unstructured data. For instance, AI-powered applications produce inaccurate outputs when fed with low-quality data.
Poor quality can turn data lakes into data swamps, thus eliminating their benefits.
Companies need to build compelling data processing capabilities to feed high-quality data into analytical tools. Building these capabilities in-house takes both time and money. With their superior data cleansing skills, MSPs can provide effective solutions to improve data quality.
5. Lack of scalability
Data lakes often require structured and organized data, which makes them less flexible and scalable. After its initial deployment, data lakes are expected to handle increasing data volumes. To build a reliable and scalable data lake, organizations must choose the right data analytics framework that can deliver real-time data access.
Additionally, a low total cost of ownership (TCO) and effective management are key requirements for scalable data lakes. With MSPs, organizations no longer need to think about how to scale up their data lakes for higher processing capabilities.
Next, let us discuss how Ellicium’s data lake services can overcome these challenges.
How Ellicium’s Data Lake Managed Services can help
To leverage their Big Data initiatives, organizations must first eliminate isolated data silos. Additionally, executives face the challenge of making the right decisions when insights must be drawn from unstructured data sources.
Here is how the Ellicium services help in implementing data lakes. The powerful Ellicium MSP offering includes:
- Customer consultation and roadmap for creating data lakes
- Implementation of data lakes using cloud technologies like Apache Hadoop, AWS, and MS Azure
- Data extraction from unstructured sources including the web, social media platforms, log files, and PDF documents
- Implementation of data lake frameworks for real-time ingestion and analysis of data from IoT devices
- Use of Big Data technologies like Kafka, Spark, and Streamsets
- Data modeling for specific business models used in data lakes
- Implementation of ETL tools like Talend and Informatica and scheduling tools like Control-M for integrating and controlling data lake processes
Here is one of our customer successes stories:
- One of the largest healthcare companies in the U.S had over 200 siloed applications. Based on MS Azure, Snowflake, and Talend, our data lake solution provided them with a 360-degree view of their patients, employees, and service providers.
Data lakes are very effective at storing data, thus offering both flexibility and scalability to data-dependent organizations. However, companies often struggle to extract business value from their data lakes, resulting in project failures. Working with a managed services partner like Ellicium can add value through their technical expertise and project experience.
At Ellicium Solutions, we design data lake solutions based on the customer’s end-user analytics and reporting requirements. With our managed services, we ensure that you have all the necessary technologies and resources to meet your business objectives. Here are 5 reasons why you need to work with a data analytics managed services partner like Ellicium.
Partner with us in your data analytics journey. Start your data journey today.