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Data lake consulting for your organization's needs

Make the most of your data lake and integrate it across your organization with Datavid's expert consulting.


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Helping world-class organizations implement data lakes

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Datavid has years of experience supporting businesses like yours in managing scattered data across systems that make it difficult to extract valuable insights. Data lakes are usually the solution to this problem.

But they're often implemented poorly.

As centralized repositories that allow for storage, management, and integration of massive amounts of data—they can get complex fairly quickly. With Datavid's help, your business can dive into the depths of its data and create a full picture of where that information goes, who gets to access it, and how it's used.

Bring data together from disparate sources

Having a lot of data is valuable, but only if it's clean, accessible, and organized.  
Thanks to Datavid's team,  your organization can have all its data in one place and unlock its full potential.

Make accessing data as easy as flipping a switch

Give your organization's team members the ability to access even complex data with the click of a button. Datavid develops software for non-technical users to achieve productive data workflows in their domain.

Enable new business opportunities

With a proper data lake,your organization has control over its enterprise assets. That means opening a host of possibilities like integrating data into products, using it for R&D, creating internal tools, and more.

Turn your data lake into a business win.

Data lakes are inherently technical, but they exist to serve a business purpose: bringing all your organization's data together and categorizing it so that it can be accessed more easily. Datavid helps you achieve just that.

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Manage your data effectively

Data lakes are designed to handle large volumes of data, unifying multiple sources in one location for easier organization and management. Datavid's consulting gives you the tools to achieve this goal successfully thanks to our consultants' deep expertise in database technology.

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Make accessing data a breeze

Datavid allows for easy and secure access to your data by multiple teams and stakeholders. Our data lake implementations democratize data access and enables self-service across the board, empowering individuals throughout your organization to use information effectively.

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Prepare data for other applications

Well-implemented data lakes are containers that allow for useful functionality like business analytics, semantic search, compliance reporting, and more. Datavid doesn't stop at creating the data lake itself—we advise your organization on how to make best use of all this data.

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Revolutionizing data management

The American Chemical Society faced the challenge of managing a vast amount of data without a general storage repository.  

Datavid proposed and developed a content lake that acted as a suitable authority and preservation repository, providing higher performance, efficiency, availability, and capacity. 

The result was an efficient storage, processing, search, and retrieval of large volumes of structured and unstructured content, that has reduced the overall costs. 

Read the full case study →

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There was so much effort behind the scenes in validating and normalizing our content that spans many generations of people, production processes, and technologies – what a feat!


Your questions. Answered.

A data lake is a centralised repository that stores a vast amount of raw and unstructured data from various sources. It allows organisations to store, process, and analyse data flexibly, making it a valuable resource for big data analytics and data-driven decision-making

Data lakes are typically managed by data engineers, data scientists, and IT professionals within an organisation. They are responsible for data ingestion, storage, security, and ensuring that data is accessible for analysis by various teams and stakeholders.

Data lakes are not replacing data warehouses but are often used in conjunction with them. Data lakes are more suitable for storing raw and unstructured data, while data warehouses are designed for structured data and optimised for analytical queries. Many organisations use both data lakes and data warehouses to meet their diverse data storage and analysis needs.

Take your organization's data practices to new heights

datavid manish gupta data engineer