Data Lake Services
What Is The Service?
Most of the enterprises have their data present in silos. Due to this, the data that is available to the decision-makers is always either incomplete or inaccurate. Also, the data presented to the decision-makers do not cater to the data that is unstructured i.e. PDF’s, docs, emails, social media etc. This has a huge impact on the decision taken by the higher management. A data lake is a centralized repository that allows storage all structured and unstructured data at any scale. Organizations can store your data as-is, without the need to structure the data, and then run different types of analytics for decision making.
Our Data Lake Services
Consulting and roadmap discussion and creation for enterprise data lake
Designing data lake layered architecture solutions keeping in mind the end user reporting and dashboard requirements as well as analytics and AI related use cases.
Setting up data lake using Big data and cloud technologies like hadoop, AWS, Azure etc
Unstructured data extraction (web, log files, social media, pdfs, etc.) from external sources and data parsing using NLP techniques and machine learning algorithms.
Frameworks for ingestion and analysis of real time and streaming data from IOT devices, logs etc using big data technologies like Kafka, Spark Streaming, Streamsets etc
Enterprise Search, discover and analysis capabilities on the data lake using technologies like SOLR and ELK stack.
Data modelling based on industry standard business specific models for the data lake
Implementation of metadata and master data management, data quality and data governance on the data lake
Implementation of ETL tools like Talend, Informatica as well as schedulers like Control-M as tools for integrating, orchestrating and scheduling the data lake processes.
Implementation of data lake security and governance, for on-premise and on-cloud implementations.
Industry standards, Best practices, reference architectures and success stories for the data lake available
How Creation of A Data Lake Helps?
In bringing data from all source systems at a single place which ultimately leads to the removal of data silos.
All kinds of data are available to the decision-makers i.e. structured, semi-structured and unstructured.
Rather than having to go to multiple source systems for data, all data is present at 1 place
The traditional approach – decide on a use case and then collect the required data
Data Lake approach – you always collect all the available data irrespective of the use case
Success Stories
Ellicium implemented Data Lake on Azure cloud using Big Data, for one of the leading US healthcare chains
