CIO Business Intelligence

AUGUST 9, 2024

They’re trying to get a handle on their data estate right now. Once they have that, they can start applying the data science and machine learning to predict how they can be more efficient with the gates,” says McKinney, who has partnered with Pruitt on the project.

Data Transformation 126

Data Transformation Machine Learning Data Lake Dashboards 126

Analytics Vidhya

JUNE 18, 2019

Overview The Transformer model in NLP has truly changed the way we work with text data Transformer is behind the recent NLP developments, including. The post How do Transformers Work in NLP? A Guide to the Latest State-of-the-Art Models appeared first on Analytics Vidhya.

Modeling 307

Modeling Data Transformation Analytics Deep Learning 307

KDnuggets

AUGUST 17, 2022

How to Perform Motion Detection Using Python • The Complete Collection of Data Science Projects - Part 2 • What Does ETL Have to Do with Machine Learning? Data Transformation: Standardization vs Normalization • The Evolution From Artificial Intelligence to Machine Learning to Data Science.

Data Science 95

Data Science Machine Learning Data Transformation 95

O'Reilly on Data

OCTOBER 19, 2021

Similarly, it would be pointless to pretend that a data-intensive application resembles a run-off-the-mill microservice which can be built with the usual software toolchain consisting of, say, GitHub, Docker, and Kubernetes. Adapted from the book Effective Data Science Infrastructure. Data Science Layers.

IT 364

IT Testing Experimentation Software 364

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics and data science are closely related.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

AWS Big Data

NOVEMBER 22, 2024

In this post, we’ll walk through an example ETL process that uses session reuse to efficiently create, populate, and query temporary staging tables across the full data transformation workflow—all within the same persistent Amazon Redshift database session. She is passionate about data analytics and data science.

Data Warehouse 105

Data Warehouse Recreation/Entertainment Cost-Benefit Data-driven 105

CIO Business Intelligence

OCTOBER 11, 2022

As one of the world’s largest biopharmaceutical companies, AstraZeneca pushes the boundaries of science to deliver life-changing medicines that create enduring value for patients and society. Before AI Bench, every data science project was like a separate IT project. Four ways to improve data-driven business transformation .

Machine Learning 145

Machine Learning Data Science Data-driven Testing 145

Jen Stirrup

SEPTEMBER 30, 2021

Although CRISP-DM is not perfect , the CRISP-DM framework offers a pathway for machine learning using AzureML for Microsoft Data Platform professionals. AI vs ML vs Data Science vs Business Intelligence. They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. The Open Data Lakehouse . Cloudera builds dbt adaptors for all engines in the open data lakehouse.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

Cloudera

JUNE 24, 2024

In the fast-evolving landscape of data science and machine learning, efficiency is not just desirable—it’s essential. Imagine a world where every data practitioner, from seasoned data scientists to budding developers, has an intelligent assistant at their fingertips.

Machine Learning 72

Machine Learning Data Science Data-driven Testing 72

AWS Big Data

NOVEMBER 13, 2023

The downstream consumers consist of business intelligence (BI) tools, with multiple data science and data analytics teams having their own WLM queues with appropriate priority values. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. This is a serverless analytics job service that can handle petabyte scale data transformation, so you pay for the job rather than needing to manage infrastructure.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

CIO Business Intelligence

DECEMBER 22, 2022

Analytics, Collaboration Software, Data Management, Data Mining, Data Science, IT Strategy, Small and Medium Business.

Analytics 130

Analytics Machine Learning Data mining Software 130

AWS Big Data

APRIL 19, 2023

The solution generates a list of data products, product attributes, and the associated probability scores to show join ability. We use Valentine, a data science algorithm for comparing datasets, to improve data product recommendations. The data science algorithm Valentine is an effective tool for this.

Technology 105

Technology Data-driven Machine Learning Sales 105

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Maintaining lists of possible values for the columns requires continuous updates.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

CIO Business Intelligence

AUGUST 3, 2023

At Paytronix, which manages customer loyalty, online ordering, and other systems for its customers, director of data science ­Jesse Marshall wanted to reduce the custom coding of data transformations—the conversion, cleaning, and structuring of data into a form usable for analytics and reports.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

Cloudera

OCTOBER 11, 2021

Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x. Modak Nabu relies on a framework of “Botworks”, a series of micro-jobs to accomplish various data transformation steps from ingestion to profiling, and indexing. Cloud Speed and Scale.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. .

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

Cloudera

AUGUST 3, 2022

By leveraging Hive to apply Ranger FGAC, Spark obtains secure access to the data in a protected staging area. Since Spark has direct access to the staged data, any Spark APIs can be used, from complex data transformations to data science and machine learning. .

Snapshot 90

Snapshot Cost-Benefit Machine Learning Data Science 90

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers. He decides to run his data journey map idea by his friend. No Journey Exists in a Vacuum.

Testing 130

Testing Data-driven Visualization Dashboards 130

Data Insight

JANUARY 21, 2020

Last year almost 200 data leaders attended DI Day, demonstrating an abundant thirst for knowledge and support to drive data transformation projects throughout their diverse organisations. This year we expect to see organisations continue to leverage the power of data to deliver business value and growth.

Internet of Things 52

Internet of Things Data Science Cost-Benefit Data Governance 52

Alation

JANUARY 17, 2023

Powered by cloud computing, more data professionals have access to the data, too. Data analysts have access to the data warehouse using BI tools like Tableau; data scientists have access to data science tools, such as Dataiku. Better Data Culture. Good data warehouses should be reliable.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

Smarten

AUGUST 13, 2024

The creation of no-code and low-code apps allows for simple foundations and construction to analyze data without customization or programming or data science skills supports both developers, data scientists and power users of analytics by providing tools to simply and easily create complex components.

Analytics 57

Analytics Cost-Benefit Predictive Modeling Dashboards 57

Sisense

AUGUST 6, 2020

As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data? What are the right KPIs and outputs for your product? What will it take to build your MVP?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Insight

APRIL 8, 2020

Having run a data engineering program at Insight for several years, we’ve identified three broad categories of data engineers: Software engineers who focus on building data pipelines. In some cases, they work to deploy data science models into production with an eye towards optimization, scalability and maintainability.

Data Warehouse 96

Data Warehouse Cost-Benefit Software Optimization 96

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever. The post NEW: Octopai Announces Support of Microsoft Azure Data Factory appeared first on Octopai.

Metadata 52

Metadata ROI Machine Learning Data Quality 52

Smarten

AUGUST 4, 2023

If your team has easy-to-use tools and features, you are much more likely to experience the user adoption you want and to improve data literacy and data democratization across the organization.

Data Lake 52

Data Lake Machine Learning Data Integration Data Quality 52

Alation

FEBRUARY 20, 2020

For ease of understanding the differences between all of the them Rita shared this visual, categorizing the vendors: So at least for now, it looks like we’re a self-service data prep vendor, which makes sense. Alation helps analysts find, understand and use their data. Back on the Ranch: Data Literacy Driven by Self-Service.

Scorecard 52

Scorecard ROI Data-driven Visualization 52

AWS Big Data

AUGUST 19, 2024

Using AWS Glue transformations is crucial when creating an AWS Glue job because they enable efficient data cleansing, enrichment, and restructuring, making sure the data is in the desired format and quality for downstream processes. Refer to Editing AWS Glue managed data transform nodes for more information.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

Cloudera

AUGUST 8, 2022

No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data. Exploratory data science and visualization: Access Iceberg tables through auto-discovered CDW connection in CML projects.

Snapshot 94

Snapshot Data Warehouse Machine Learning Cost-Benefit 94

AWS Big Data

AUGUST 6, 2024

Example data The following code shows an example of raw order data from the stream: Record1: { "orderID":"101", "email":" john. To address the challenges with the raw data, we can implement a comprehensive data transformation process using Redshift ML integrated with an LLM in an ETL workflow.

Data Warehouse 104

Data Warehouse Data-driven Modeling Internet of Things 104

Jet Global

MAY 28, 2019

But the foundational step in getting the data to drive your business forward is first ensuring it can be collected and identified in a way that makes it simple to find and report on with the insights that matter. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

IBM Big Data Hub

JULY 17, 2023

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Metrics 52

Metrics Dashboards Sales Reporting 52

DataRobot Blog

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

IBM Big Data Hub

OCTOBER 16, 2023

A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence. It helps you streamline data engineering with reduced data pipelines, simplified data transformation and enriched data.

Risk 70

Risk Modeling Management Metadata 70