Data Lakes

A good data lake can accelerate an organization’s journey towards advanced analytics by enabling value-added data innovation and exploration.

Effective data lakes are built from a business-first perspective, using proper data management and scalable capacity.


Lingaro’s Data lakes process data fast at scale with visual reporting, exploratory analysis and point-and-click accessibility, truly supporting every business user – not just data scientists or IT staff.

Data Challenges

Modern challenges with data are major bottlenecks:

Limited scalability, with the need to serve unlimited volumes of data (Big Data);
Poor Usability of Siloed Data;
Issues with connecting new sources;
Lack of technical foundations to support advanced analytics;
Flexibility of existing Data Warehouse ecosystem;
Performing advanced analytics;
Oversaturated with Data – Data Swamp;
Poor-quality data caused by master data adjustment challenges.

We understand your
as we meet
them in practice

Questions frequently asked by our clients:

„Should I get rid of all commodity DW solutions when moving to Cloud and Data Lake?”

„Our problem seems to be that we are building data as part of projects in isolation.”

„Should all the structured, precalculated and pre-aggregated data from EDW be loaded to Data Lake?”

„How to implement an effective Data Governance Policy?”

„I still do not see how I would avoid siloed data with Data Lake.”

„How can we improve performance with DL and DW solutions?”

„If we load all the data, there is a high chance of creating lots of duplicates. Should we care?”

„With time, I’d expect the same complexity as with the traditional Data Warehouse approach.”

„Do you have to have the end state in mind while building the Data Lake?”

„Why is Data Lake more flexible?”

Lingaro Offer

Check out how we delivered the largest Azure data lake to date for a high-profile FMCG client

Download case study →

Data Lake Case Study

Trusted Technology Partner

Lingaro partners with clients to overcome even the most complex data lake challenges. Regardless of your current deployment stage, we are able to accelerate your time-to-value with best practices learned executing data lake projects of all sizes, from global rollouts to one-off optimizations.

We provide data lake platform and data governance consulting that ensures:


Proper data governance and data management

Democratized access to data with elimination of data silos in the organization

Data security ensured for each level of data sensitivity (eg. PII data) with access rights granted by business role


Easier experimentation and better business focus with a use-case-based approach

A single view of up-to-date KPIs – based on data smoothly drawn from multiple sources – supporting crucial decisions

Trusted master data meeting specific local needs without compromising global reporting capabilities


Flexibility for users to run improved analytics on raw data with better insights and understanding in the future

Quick delivery of integrated datasets for data science, advanced analytics, and BI applications

Seamless integration of existing data processes with new data from BI applications introduced in the future


Effective data integration that makes it easy to translate raw data into actionable insights with leading self-service BI tools

Long-term cost savings in terms of infrastructure / hardware and their support

A data lake that can be incorporated into the current IT landscape with data hubs and data warehouses

How we work

Lingaro believes that adoption is a key business aspect to every analytics solution, including data lake implementations. Without a clear understanding of its benefits, data lakes hold a high risk of failure.

Therefore, by implementing Lingaro’s Adoption-First Method, we make sure that strategic requirements are covered, and that the solution is used from its first days. We develop a strategy and roadmap for Data Lake expansion and start the implementation from a chosen business function (i.e. sales, supply chain) MVP.

Data Lake transformation steps and milestones

01. MVP
The Minimum Viable Product satisfies critical business needs with sufficient functionalities. Its iterative building process allows for prompt feedback for further product evolution. Fast time to value is one of the key objectives and expectations.
02. Evolution
In this phase, new data types are added and more focus is put on common understanding, consistency, and the accuracy of data.
03. Expansion
Based on the learning experiences, new enhancements and features are proposed and implemented. Work is focused on Data Lake use case expansion and further adoption at the same time making sure that settled users are not impacted by the changes.
04. Sunset
The sunset phase gives the opportunity to phase out the legacy systems that were part of the transformation journey.

Key Benefits

With the right data lake, a company can launch advanced analytics and BI solutions faster and dramatically reduce its time-to-insights. Based on user feedback from our key clients, top benefits include:

Business Benefits

All data brought together;
Trusted, quality data;
High adoption among decision makers to support both daily and strategic decisions;
Democratized access to data & elimination of data silos;
Speed of getting data and insights (fast time-to-value);
Real-time decision analyses.
Technology Benefits

Smooth real-time dataflow;
Supporting SQL and other languages;
Versatile (structured and un-structured data).

Check out our infopack to learn more about us, what we do, and how we do it.

Download case study →


data lakes

Data Lakes powered
by Cloud Architecture

Despite the general growing reliance on the cloud – our experiences show that – many companies still don’t take advantage of cloud-base architecture to build high level scalability and optimize their infrastructure costs.

Lingaro has large experience in incorporating cloud environments to implement Big Data and Data Lakes. Building applications in the Cloud minimize Capital Expenses incurred before the development is made. We build solutions with scalability and performance in mind – making sure that solution that we deliver can be extended to new markets/regions faster, secure and without interrupting performance.

Lingaro Case Study

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Here are examples on how the Data Lake may be implemented using tools from two major Cloud providers – Amazon Web Service (AWS) and MS Azure.

Download our infopack →

Our Cloud Technology Partners

(among others)

Partner with us

while building Data Lakes and Cloud Transformation projects

We offer a unique mixture of startup agility and operational excellence of mature organization

We offer proven tracks of successful delivery of DevOps services to global customers

Lingaro delivers impressive improvements through a unique approach towards DevOps services

Services tailored towards actual customer needs

Lingaro approach to data-lake development can help your company launch analytics programs quickly and establish a data-friendly culture for the long term.

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we can help.
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