2017 and Data Preparation - Data Science Current

Augmented analytics

Dataconomy

MARCH 17, 2025

This technological advancement not only empowers data analysts but also enables non-technical users to engage with data effortlessly, paving the way for enhanced insights and agile strategies. Augmented analytics is the integration of ML and NLP technologies aimed at automating several aspects of data preparation and analysis.

Augmented Analytics

Augmented Analytics Analytics Analytics Natural Language Processing

3 Major Trends at Strata New York 2017

DataRobot Blog

OCTOBER 3, 2017

Standard Chartered Bank’s Global Head of Technology, Santhosh Mahendiran , discussed the democratization of data across 3,500+ business users in 68 countries. Interactively explore, combine, and shape diverse datasets into data ready for machine learning and AI applications. Try now for free.

Data Lakes

Data Lakes Azure Data Pipeline Hadoop

A secure approach to generative AI with AWS

AWS Machine Learning Blog

APRIL 16, 2024

Its specialized hardware and associated firmware are designed to enforce restrictions so that nobody, including anyone in AWS, can access your workloads or data running on your Amazon Elastic Compute Cloud (Amazon EC2) instances.

AWS

AWS AI AI ML

Webinars

Agent Tooling: Connecting AI to Your Tools, Systems & Data

Automation, Evolved: Your New Playbook for Smarter Knowledge Work

How to Modernize Manufacturing Without Losing Control

Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

MORE WEBINARS

5 Hardware Accelerators Every Data Scientist Should Leverage

Smart Data Collective

APRIL 5, 2022

Although SageMaker has become a popular hardware accelerator since it was launched in 2017, there are plenty of other overlooked hardware accelerators on the market. If you want to streamline various parts of the data science development process, then you should be aware of all of your options.

Data Scientist

Data Scientist Data Science Machine Learning Machine Learning

Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

Data Visualization

Deploy large language models for a healthtech use case on Amazon SageMaker

AWS Machine Learning Blog

FEBRUARY 6, 2024

In this section, we describe the major steps involved in data preparation and model training. Data preparation We used the Adverse Drug Reaction Data ( ade_corpus_v2 ) within the Hugging Face dataset with an 80/20 training/test split.

AWS

AWS ML ML Data Preparation

AWS positioned in the Leaders category in the 2022 IDC MarketScape for APEJ AI Life-Cycle Software Tools and Platforms Vendor Assessment

AWS Machine Learning Blog

JANUARY 6, 2023

The vendors evaluated for this MarketScape offer various software tools needed to support end-to-end machine learning (ML) model development, including data preparation, model building and training, model operation, evaluation, deployment, and monitoring.

AWS

AWS ML ML Data Preparation

3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

APRIL 1, 2018

This new platform will also serve many different use cases, including but not limited to analytics, application and data migrations, data monetization, and master data creation. . [1] 1] Gartner, Augmented Analytics Is the Future of Data and Analytics , Published: 27 July 2017, Analyst(s): Rita L.

Analytics

Analytics Analytics Data Preparation Augmented Analytics

Building your own Object Detector from scratch with Tensorflow

Mlearning.ai

MARCH 31, 2023

Data augmentation, data preparation, Feature Engineering, etc also play an important role in this game. In the context of our object detector, the model, the data, the metrics and the training are covered in the next sections. This is basically the path in which we are going to walk here.

Deep Learning

Deep Learning Deep Learning Machine Learning Machine Learning

New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

Analytics

Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Tableau

JANUARY 27, 2021

In the recent Gartner Peer Insights ‘Voice of the Customer’: Data Preparation Tools report , Tableau is the only vendor recognized in the Gartner Peer Insights Customers’ Choice distinction across all regions, company sizes, and industries—including the sole Customers’ Choice by users in the finance vertical. .

Tableau

Tableau Business Intelligence Business Intelligence Analytics

Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Tableau

JANUARY 27, 2021

In the recent Gartner Peer Insights ‘Voice of the Customer’: Data Preparation Tools report , Tableau is the only vendor recognized in the Gartner Peer Insights Customers’ Choice distinction across all regions, company sizes, and industries—including the sole Customers’ Choice by users in the finance vertical. .

Tableau

Tableau Business Intelligence Business Intelligence Analytics

The year of the data catalog

Alation

FEBRUARY 13, 2020

In his research report, From out of nowhere: the unstoppable rise of the data catalog 5, Analyst Matt Aslett makes a strong case for data catalog adoption calling it the “most important data management breakthrough to have emerged in the last decade.”. Duncan, December 13, 2017. The coming year promises more greatness!

Data Governance

Data Governance Machine Learning Machine Learning Analytics

A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Thirdly, the presence of GPUs enabled the labeled data to be processed. In 2017, the landmark paper “ Attention is all you need ” was published, which laid out a new deep learning architecture based on the transformer. In order to train transformer models on internet-scale data, huge quantities of PBAs were needed.

AWS

AWS ML ML Clustering

Embodied AI Chess with Amazon Bedrock

AWS Machine Learning Blog

NOVEMBER 27, 2024

This approach to data preparation creates the foundation for fine-tuning a model that can play chess at a high level. Fine-tune a model With our refined dataset prepared from successful games and legal moves, we now proceed to fine-tune a model using Amazon SageMaker JumpStart.

AWS

AWS AI AI Python

Data Science Current

Augmented analytics

3 Major Trends at Strata New York 2017

Webinars

Trending Sources

A secure approach to generative AI with AWS

Webinars

5 Hardware Accelerators Every Data Scientist Should Leverage

Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Deploy large language models for a healthtech use case on Amazon SageMaker

AWS positioned in the Leaders category in the 2022 IDC MarketScape for APEJ AI Life-Cycle Software Tools and Platforms Vendor Assessment

3 Takeaways from Gartner’s 2018 Data and Analytics Summit

Building your own Object Detector from scratch with Tensorflow

New Study: 2018 State of Embedded Analytics Report

Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

Tableau: 9 years a Leader in Gartner Magic Quadrant for Analytics and Business Intelligence Platforms

The year of the data catalog

A review of purpose-built accelerators for financial services

Embodied AI Chess with Amazon Bedrock

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