Maximize the productivity of your Data Scientists

The roles of a Data Scientist involve the elaboration of predictive models to make data understandable and exploitable for the company’s top management, and also to build machine learning algorithms.

In order to succeed, collaborators must be able to determine what data is available and what data they really need. They also need to understand the data (context and quality), as well as knowing how to retrieve it!

Unfortunately, surveys suggest that roughly 80% of a Data Scientists’ time is spent cleaning, finding, and understanding data instead of analyzing it…

Simplify data discovery for your Data Scientists

 In order to bring meaning and context around data assets, it is essential for an organization to be tooled up with a data catalog.

 Zeenea’s platform allows your Data Scientists, among other things, to find, identify and understand data from an intuitive interface.

A SMART SEARCH ENGINE

Retrieve your datasets in minutes

Our data catalog indexes, and automatically updates the content of any data set through the Zeenea platform from the storage systems its connected to.

Just like Google, Data Scientists have access to a search engine to accelerate and simplify the discovery of relevant data sets for their use cases.

Simply type in a keyword, add a few filters, click search to find the data sets you need.

give your data context

Work with the right information

 

Zeenea’s features allow data Data Scientists to understand the context around their data sets.

Metadata imported automatically or manually entered by the Data Steward in our data catalog allows anyone to verify the relevance or even the quality of a data set for their use case.

A Data Scientist can also study the relationships associated with a data asset through our data lineage feature, a visual representation of the lifecycle of the data.

EXPLORE YOUR USE cASES

Collaborate on data science projects

We offer a collaborative data catalog for the Data Scientists to share
their knowledge on datasets and their uses.

All the different data profiles (CDO, Data Steward or even a Data Analyst) tthus participate in the construction and improvement of knowledge of the enterprise’s data assets.

Sharing information and feedback in our data catalog empower Data
Scientists to make the best decisions when choosing which datasets
to use.

Find out more about Data Scientists

Data science: accelerate your data lake initiatives with metadata

Data lakes offer an unlimited storage for data and present lots of potential benefits for data scientists in the exploration and creation of new analytical models. However, this structured, unstructured and semi-structured data are mashed together and the business insights they contain are often overlooked or misunderstood by data users.

The reason for this is that many technologies used to implement data lakes lack the necessary information capabilities that organizations usually take for granted. It is therefore necessary for these enterprises to manage their data lakes by putting in place effective metadata management which considers metadata discovery, data cataloguing, and overall enterprise metadata management applied to the company’s data lake.

Read our blog post

How a business glossary empowers your data scientists

In the data world, a business glossary is a sacred text that represents long hours of hard work and collaboration between the IT & business departments. In metadata management, it is a crucial part of delivering business value from data. According to Gartner, It is one of the most important solutions to put in place in an enterprise to support business objectives.

To help your data scientists with their machine learning algorithms and their data initiatives, a business glossary provides clear meanings and context to any data or business term in the company.

Read our blog post

Data Discovery through the Eyes of Tech Giants

Through automated capabilities, data discovery allows data & analytics teams to discover patterns and trends to harness and exploit data for quicker and better decision making. Knowing this, enterprises all over the world, both big and small, have started adopting data discovery solutions within their organizations.

Whether they are developed internally, or bought from Data Discovery vendors, it is no secret that this challenge isn’t just a new data buzzword, but an essential way for companies to become data driven.

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