By: Kaushal Damle, Senior Consultant

Over the past 15+ years, we have witnessed an explosion in data, especially after the advent of the cloud, mobile technology, and faster Internet. Legacy systems, which are still in use, tend to create silos or data islands. Companies today have an ecosystem with multiple applications and processes dedicated to various types of transactions. However, every company’s goals remain the same – increasing the bottom line, boosting market share, enhancing customer satisfaction through a better digital experience, reducing time-to-market for their products, and faster analysis and decision-making to improve the alpha, which is a measure of efficiency over peers and the market.

Why data lakes are better

In a typical setup, data is spread across multiple business lines and data owners. This results in data silos or islands that do not talk to each other. Such data islands are non-coherent systems that cause a negative impact and are a major hindrance in achieving the above-mentioned company goals. As mentioned, data islands are usually formed because of data silos wherein each department or business unit owns and uses the data. Data accessibility and sharing often become a challenge in such a scenario.

On the other hand, a data lake is a repository that has a flat, raw, and mostly unstructured approach. It is more flexible than traditional data stored in tables and dimensions. Introducing a data lake in your enterprise ecosystem can serve as a huge advantage and can produce a critical edge over the competition. Data lakes can take any organization closer to achieving universal company goals with significant cost and time savings.

The major benefit of data lakes is enhanced accessibility of data, including raw data. Data consumers can have a single window of access to data, thereby reducing costs and time substantially.

To quote just a few use cases where there are delays and sub-par user experiences due to data silos:

• A fund manager trying to launch a fund and run a campaign for it.
• Product launches and marketing campaigns, market research, and surveys.
• Data availability and accessibility required for the analysis of ‘make or buy’ or ‘buy and maintain’ decisions.
• Target and customer analysis before any campaign.
• Accessing static, transactional, and analytical data for a better customer experience.
• Client reporting, feedback and analysis, and regulatory reporting requirements.
• Setting up e-voting for shareholders.

Data Warehouse vs. Data Lake:

Data lakes and warehouses have their own unique characteristics:

While a data lake sounds similar to a data warehouse, it has its own unique benefits and challenges.

Benefits:

• It enables users to create models on the fly.
• Data lakes entail lower costs because there are many open-source technologies that
  can be utilized to reduce costs.
• As a lake with multiple data sources, this environment can carter to large-scale
  analytics, modeling, machine learning, enhanced mining, and real-time data access for analysis.

Challenges

• Data lakes have a tendency to turn into data dumps if not managed properly.
• It is a relatively new concept, and the tools and technology that are used to create and manage a data lake can be very expensive and challenging if not planned properly.
• There can be challenges in maintaining and servicing of data, which can result in
  incorrect analysis.

Conclusion:

Although data lakes are still in their infancy, they entail lower costs because of their unstructured nature with multiple data sources. If implemented correctly, the full potential of raw and real-time data can be leveraged to enhance user experience. This will ultimately have a positive impact on an enterprise’s bottom-line.

Moreover, a data lake need not exist in isolation. With the right partner, a data lake can also be tailored with a unique mix and match with a conventional warehouse, thus addressing the existing challenges while leveraging existing systems.

How LTIMindtree can help:

References:

• IT Services: IT Solutions & Technology Consulting Company | LTIMindtree
• https://www.datacamp.com/
• https://www.techtarget.com/