Cloudera

AUGUST 25, 2020

Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon. One of the key takeaways from recent times that should be considered into the future, is that banks need to rethink how they look at tail risk or extreme events that rarely happen. .

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Prescriptive Analytics Technology Machine Learning Risk 71

Andrew White

JANUARY 11, 2021

It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. The fill report is here: Leadership Vision for 2021: Data and Analytics. Which industry, sector moves fast and successful with data-driven?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

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Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques.

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IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. Adoption is imperative to beat the competition, release innovative products and services, better meet customer expectations, reduce risk and fraud, and drive profitability. Start a trial. AI governance.

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Data-driven Enterprise Data Governance Prescriptive Analytics 56

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

Domino Data Lab

JUNE 2, 2019

She had much to say to leaders of data science teams, coming from perspectives of data engineering at scale. And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. Because of compliance. " – Prof.

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Data-driven Data Science Machine Learning Modeling 110