Andrew White

MAY 4, 2020

Demand from all these organizations lead to yet more data and analytics. However, the AI, data and analytics of 2020 are a quite different to what was being adopted or sought just 6 months ago in 2019, Somethings in D&A have changed completely; somethings not prioritized before are now required.

Uncertainty 90

Uncertainty Data Quality Consulting Predictive Modeling 90

Smarten

FEBRUARY 28, 2019

If Data Science was once the sole domain of analysts and data scientists, Augmented Data Science represents the democratized view of this domain. Augmented data science automates and simplifies analysis with machine learning so implementation, training and adoption of these tools is rapid and successful.

Data Science 40

Data Science IT Machine Learning Predictive Modeling 40

Smarten

JANUARY 17, 2020

As one of its Strategic Assumptions, Gartner predicted that ‘By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’ Look for Self-Serve Data Preparation , Smart Data Visualization , and Assisted Predictive Modeling.

Analytics 52

Analytics Predictive Modeling Business Analysis Visualization 52

CIO Business Intelligence

MAY 10, 2022

billion in November 2020. Segment is a data-integration CDP designed to collect data and then distribute it in real time to other systems. Treasure Data CDP. Treasure Data CDP is a data science CDP built for predictive modeling and advanced analytics.

Advertising 122

Advertising Interactive Marketing Structured Data 122

Birst BI

AUGUST 23, 2018

What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases? Automating data science tasks leaves room to build more AI applications with the same amount of data science resources. Source: Gartner (April 2018).

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Smarten

JANUARY 24, 2019

Business users can leverage machine learning and assisted predictive modeling to achieve the best fit and ensure that they use the most appropriate algorithm for the data they wish to analyze. Not so long ago, this type of Advanced Analytics would have demanded the services of a full-time, trained data scientist.

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

Cloudera

MAY 12, 2021

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. We saw a record number of entries and incredible examples of how customers were using Cloudera’s platform and services to unlock the power of data. INDUSTRY TRANSFORMATION.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

CIO Business Intelligence

MARCH 22, 2023

Instead of sending data to a central server for processing, the training occurs locally on each device, and only model updates are transmitted to a central server. Additionally, federated learning does not address the inference stage, which still exposes data to the ML model during cloud or edge device deployment.

Machine Learning 105

Machine Learning Cost-Benefit Modeling Risk 105

Smarten

FEBRUARY 7, 2019

The Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics, published on October 31, 2018, includes the following strategic assumptions: By 2025, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.

Optimization 40

Optimization Analytics Predictive Modeling Data Science 40

Smarten

MARCH 19, 2019

The Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics, published on October 31, 2018, includes the following strategic assumptions: By 2020, augmented analytics will be a dominant driver of new purchases of analytics and BI as well as data science and machine learning platforms, and of embedded analytics.

ROI 40

ROI Analytics Cost-Benefit Predictive Modeling 40

BI-Survey

JANUARY 29, 2023

In the context of corporate planning, predictive planning and forecasting, it is therefore a major trend to use predictive models based on statistical methods and ML for forecasting and thorough analysis. Managers need to approve and commit resources, but also understand the benefits and limitations of predictive models.

Forecasting 52

Forecasting Predictive Modeling Measurement Finance 52

O'Reilly on Data

MAY 18, 2020

Garbage in, garbage out still holds in 2020. The most common types of AI systems are still only as good as their training data. If there’s no historical data that mirrors our current situation, we can expect our AI systems to falter , if not fail. All predictive models are wrong at times?—just

Risk 364

Risk Modeling Data Processing Reporting 364

Domino Data Lab

AUGUST 1, 2021

This leads to an important question – does the increased model performance outweigh other important criteria that should be taken into consideration as part of the decision making process. 2020) propose the following foundational set of methods to classify various approaches for explaining deep ANNs. References. Ribeiro, M.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139