Evolving Role of Data Scientist in the Age of Personalization

March 12, 2020

This point of view is an exploration of the possibilities engendered by rethinking the role of data scientists in the wake of industrial revolution. It might be claimed that current trends in industrial revolution reflect a paradigm shift towards data centric processing with data science playing an increasingly critical role. This point of view also explicitly highlights the potential role of Data scientists as an emerging phenomenon, and then to show some of the benefits that this role can bring as we move towards industrial disruption

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Sandtable

Sandtable is a data science company that specialises in creating models of human behaviour. We use them to help organisations understand what might happen in the future and how they can best adapt to or influence that future. Our models are built using a technique called Agent Based Modelling (ABM). We bring together data and insight from a range of sources to create explicit representations of the populations we are trying to understand. They are not ‘black boxes’ – we are seeking to uncover and represent the underlying causal mechanisms that make people do what they do.

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Introducing Apache Druid

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.

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Are Predictive Analytics Truly Predictive?

whitePaper | April 19, 2023

Unplanned downtime is one of the most significant pain points for industrial manufacturers today, costing them an estimated $50 billion each year. The risk is even greater for process manufacturing, where a critical equipment failure could result in the loss of an entire batch, environmental hazards, or safety risks. The adoption of digital technologies, such as the industrial internet of things (IIoT), promises to mitigate these threats by forecasting equipment failures and catching faults before they lead to unscheduled shutdowns. However, in practice, several challenges arise when maintenance personnel and operations leaders work to implement an IIoT solution aimed at eliminating unplanned downtime.

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Replanteamiento del acceso a las aplicaciones gestión de una fuerza laboral moderna

whitePaper | February 26, 2020

El cambio de paradigma que se está extendiendo por el ámbito tecnológico y empresarial es cada día más evidente. La transición a cloud computing está llegando a su punto de inflexión. Las fusiones y adquisiciones han proliferado. Además, con un número cada vez mayor de usuarios finales que operan fuera del entorno empresarial, los departamentos de TI deben prestar servicio a un ecosistema de usuarios cada vez más diverso, distribuido y exigente

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The Definitive Guide to Test Data Management

whitePaper | November 10, 2022

In this hyper-competitive era, faster time-to-market plays a vital role in the success of an organization. Any lag accounts for the 'Cost of delay,' impacting the value a product could create otherwise. This is the primary reason teams are adopting an agile approach to software development, testing, and release. Unfortunately, teams that don't follow suit find it challenging to deal with this accelerated timeframe.

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Data & AI Survey Report 2021/2022

whitePaper | September 2, 2022

This year, unlike previous years, we asked professionals the most difficult elements of a successful data strategy instead of the most important.

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Analytical Data Infrastructure MarketStudy (Excerpt)

whitePaper | June 23, 2021

Analytical data infrastructure (ADI) platforms underpin key analytics models via processes like data integration, preparation, management, and storage. But with complex cloud architectures, as-a-service offerings, and innovative new analytics and process developments, how can the discerning expert choose the right ADI offerings for their business?

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Spotlight

Sandtable

Sandtable is a data science company that specialises in creating models of human behaviour. We use them to help organisations understand what might happen in the future and how they can best adapt to or influence that future. Our models are built using a technique called Agent Based Modelling (ABM). We bring together data and insight from a range of sources to create explicit representations of the populations we are trying to understand. They are not ‘black boxes’ – we are seeking to uncover and represent the underlying causal mechanisms that make people do what they do.

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