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Data Lakes

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

Lingaro’s Data Lakes process data at scale, fast, with visual reporting, exploratory analysis, and with point-and-click accessibility; 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)
Siloed Data, not easily available for cross-function reporting
Issues with connecting new sources
Lack of technical foundations to support advanced analytics
Inefficient advanced analytics
Lack of flexibility of the existing Data Warehouse ecosystem
Oversaturated with Data – Data Swamp
Poor-quality data caused by master data adjustment challenges

We understand your
challenges
as we meet
them in practice

Concerns and 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 →

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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. Our best practices have been acquired by 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:

    Security

    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 (e.g. PII data) with access rights granted by business role

    Usability

    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

    Efficiency

    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

    Savings

    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 the 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

    MVP
    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.
    evolution
    02. Evolution
    In this phase, new data types are added, and more focus is put on common understanding, consistency, and the accuracy of data.
    expansion
    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.
    sunset
    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, advanced analytics and BI solutions can be launched faster and dramatically reduce time-to-insights. Key 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
    SQL and other languages supported
    Scalable solution
    Secure data and processes
    Versatile (structured and unstructured) data

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

    Download case study →

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    Infopack

      data lakes

      Data Lakes Powered
      by Cloud Architecture

      Lingaro has more than 10 years of experience in incorporating cloud environments and implementing Big Data and Data Lakes. Building applications in the Cloud minimizes capital expenses incurred before the development is made. We build solutions with scalability and performance in mind, ensuring that the delivered solution can be extended to new markets and regions faster, more securely, and without performance interruptions.

      Download
      Lingaro Case Study

        Download Case Study

          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 Include:

          Partner With Us

          for your Data Lake and Cloud Transformation projects

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

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

          We deliver impressive improvements through a unique approach towards DevOps services

          We deliver services tailored towards actual customer needs

          Lingaro’s Data-Lake development can help your company launch analytics programs quickly and establish a longstanding data-friendly culture.

           

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