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Unearth the value in your organization's data

Drive actionable business knowledge from your data with Datavid's expert analytics services and solutions.

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Helping world-class organizations implement data analytics

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Great data analytics allow you to turn your organization's raw data into actionable insights to identify patterns, trends, and opportunities that would otherwise go unnoticed. This can lead to more informed decision-making, increased efficiency, and improved performance.

Datavid accompanies you in this journey by providing you with the tools to understand, evaluate, and improve your enterprise knowledge.

Unlock hidden patterns and trends

From strategic planning to day-to-day operations, Datavid’s data analytics solutions provide you with valuable insights that can inform decision-making at all levels.

Spot and resolve costly inefficiencies 

By analyzing your data, Datavid can help you identify opportunities for optimization, leading to increased efficiency and cost savings.

Better understand your customers

Get to know your audience through the data you collect and offer them services specifically tailored to their needs—improving their experience and your bottom line.

Transform your data into a strategic asset.

With data analytics, your organization can gain insights and turn data into actionable insights that can help you achieve your business goals and stay ahead of the competition. 

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Enable decision-making at scale

With Datavid's bespoke data analytics solutions, your organization can make decisions based on insights derived from large volumes of data. This allows your company to understand trends, identify potential risks, and make the right choices for your business.

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Improve operational efficiency

Datavid can help identify inefficiencies and bottlenecks in your data architecture, allowing you to optimize processes and reduce costs. With an efficient data pipeline, your organization benefits from information that's relevant, regularly updated, and immediately accessible. 

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Improve your customers' experience

Good data analytics help you better understand your customers' needs and preferences, allowing you to tailor your products and services to meet those needs. Datavid has the expertise to develop the functionality to extract those insights while making the most of your existing infrastructure.

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CASE STUDY

Extracting knowledge from decades of data

With almost 50 thousand team members spread across the globe, Syngenta is a powerhouse in farming and agrochemicals—a dominant leader in many of its applications worldwide.

Syngenta came to Datavid with a huge challenge to solve: indexing more than 16 million files spread across dozens of data sources which contained decades worth of siloed knowledge.

Datavid developed a semantic data platform for Syngenta, with the capability to index and retrieve specific agrochemical concepts extracted from "foam tree" ontologies.

The result was a drastic reduction in research time from several weeks to just a few hours, enabling research across a vast body of knowledge previously unavailable to the R&D team.

Read the full case study →

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Datavid is helping Syngenta's scientists identify concepts that are relevant to their research more quickly, ultimately saving time and effort on a weekly basis.

Graham Mullier

HEAD OF CONTENT DIGITISATION, SYNGENTA

Your questions. Answered.

Data analytics involves the process of examining and interpreting data to discover meaningful patterns, insights, and trends. It helps organisations make informed decisions, identify opportunities, and solve problems based on data-driven evidence.

The four main types of data analytics are:
1) Descriptive Analytics: Examining historical data to understand what has happened in the past.
2) Diagnostic Analytics: Identifying why something happened by analysing data for root causes.
3) Predictive Analytics: Forecasting future trends and outcomes based on historical data and statistical modelling.
4) Prescriptive Analytics: Providing recommendations or actions to optimise decision-making and achieve specific goals.

Analysing sales data to identify which products are the most popular among different customer segments and using that information to optimise marketing strategies is an example of data analysis.

Take your organization's data practices to new heights

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