Analytics Vidhya

DECEMBER 28, 2022

Introduction Though machine learning isn’t a relatively new concept, organizations are increasingly switching to big data and ML models to unleash hidden insights from data, scale their operations better, and predict and confront any underlying business challenges.

Machine Learning 324

Machine Learning Analytics Big Data Modeling 324

CIO Business Intelligence

MAY 7, 2024

When it broke onto the IT scene, Big Data was a big deal. Still, CIOs should not be too quick to consign the technologies and techniques touted during the honeymoon period (circa 2005-2015) of the Big Data Era to the dust bin of history. Data is the cement that paves the AI value road. Data is data.

Big Data 131

Big Data Statistics Machine Learning Data Science 131

Analytics Vidhya

FEBRUARY 1, 2024

Introduction In a groundbreaking move, Alibaba Cloud has introduced a serverless version of its Platform for AI-Elastic Algorithm Service (PAI-EAS) at the AI & Big Data Summit in Singapore.

Big Data 317

Big Data Enterprise Modeling Analytics 317

Analytics Vidhya

MARCH 1, 2023

It manages huge volumes of data across many commodity servers, ensures fault tolerance with the swift transfer of data, and provides high availability with no single point of failure.

Big Data 317

Big Data Modeling Management Analytics 317

CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Smart Data Collective

SEPTEMBER 13, 2023

Welcome to 2023, the age where screens are more than mere displays; they’re interactive communication portals, awash with data and always hungry for more. The Intersection of Display and Data Let’s first establish what we’re talking about when we mention digital signage. It’s All About the Data, Baby!

Big Data 126

Big Data Analytics Interactive Advertising 126

Analytics Vidhya

MARCH 4, 2024

Introduction How do you tackle the challenge of processing and analyzing vast amounts of data efficiently? This question has plagued many businesses and organizations as they navigate the complexities of big data. From log analysis to financial modeling, the need for scalable and flexible solutions has never been greater.

Big Data 291

Big Data Modeling Analytics 291

AWS Big Data

APRIL 8, 2025

We will explore Icebergs concurrency model, examine common conflict scenarios, and provide practical implementation patterns of both automatic retry mechanisms and situations requiring custom conflict resolution logic for building resilient data pipelines. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Snapshot 117

Snapshot Management Metadata Big Data 117

Analytics Vidhya

NOVEMBER 30, 2021

Introduction to ETL ETL is a type of three-step data integration: Extraction, Transformation, Load are processing, used to combine data from multiple sources. It is commonly used to build Big Data. In this process, data is pulled (extracted) from a source system, to […].

Big Data 382

Big Data Data Science Data Integration Publishing 382

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Testing and Data Observability.

Testing 300

Testing Machine Learning Consulting Data Science 300

O'Reilly on Data

FEBRUARY 4, 2019

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). Machine Learning model lifecycle management.

Machine Learning 279

Machine Learning Enterprise IoT Big Data 279

Analytics Vidhya

FEBRUARY 2, 2023

Introduction Big data processing is crucial today. Big data analytics and learning help corporations foresee client demands, provide useful recommendations, and more. Hadoop, the Open-Source Software Framework for scalable and scattered computation of massive data sets, makes it easy.

Big Data 306

Big Data Software Data Processing Data Analytics 306

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. The model and the data specification become more important than the code.

Machine Learning 363

Machine Learning Statistics Data Quality Data Collection 363

Analytics Vidhya

JUNE 26, 2023

Introduction “Data Science” and “Machine Learning” are prominent technological topics in the 25th century. The surge of Big Data has ushered in a new era, where businesses grapple with massive amounts of data measured in petabytes […] The post What is the Difference Between Data Science and Machine Learning?

Machine Learning 323

Machine Learning Data Science Big Data Measurement 323

DataKitchen

DECEMBER 7, 2021

Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, by Randy Bean. Data Teams: A Unified Management Model for Successful Data-Focused Teams, by Jesse Anderson. the data scientist, the engineer, and the operations engineer). How did we get here?

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

O'Reilly on Data

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Machine Learning 337

Machine Learning Testing Modeling Cost-Benefit 337

O'Reilly on Data

APRIL 9, 2019

Otherwise, this leads to failure with big data projects. They’re hiring data scientists expecting them to be data engineers. She stares at overly simplistic diagrams like the one shown in Figure 1 and can’t figure out why Bob can’t do the simple big data tasks. Conversely, most data scientists can’t, either.

Data Science 280

Data Science Big Data Management ROI 280

Analytics Vidhya

JANUARY 3, 2022

Table of Contents Introduction Machine Learning Pipeline Data Preprocessing Flow of pipeline 1. Loading data into Cloud Storage 3. Loading Data Into Big Query Training the model Evaluating the Model Testing the model Summary Shutting down the […]. Creating the Project in Google Cloud 2.

Machine Learning 380

Machine Learning Testing Data Science Publishing 380

CIO Business Intelligence

DECEMBER 11, 2024

Digital transformation started creating a digital presence of everything we do in our lives, and artificial intelligence (AI) and machine learning (ML) advancements in the past decade dramatically altered the data landscape. AI/ML models now power customer-facing products with sub-second response times.

Management 111

Management Data Governance Data Science Reporting 111

Analytics Vidhya

NOVEMBER 25, 2022

This article was published as a part of the Data Science Blogathon. Source:pixabay.com Introduction State-of-the-art machine learning models and artificially intelligent machines are made of complex processes like adjusting hyperparameters and choosing models that provide better accuracy and the metrics that govern this behavior.

Machine Learning 328

Machine Learning Metrics Data Science Publishing 328

Analytics Vidhya

SEPTEMBER 1, 2022

The most common reason is to cause a malfunction in a machine learning model; an adversarial attack might entail presenting a model with inaccurate or misrepresentative data as its training or introducing maliciously designed data to deceive an already […].

Machine Learning 374

Machine Learning Modeling Analytics IT 374

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

AWS Big Data

NOVEMBER 27, 2024

The Zero-ETL integration between Aurora MySQL and Amazon Redshift is set up by using a CloudFormation template to replicate raw ticket sales information to a Redshift data warehouse. These insights help analysts make data-driven decisions to improve promotions and user engagement. Create dbt models in dbt Cloud.

Data Warehouse 94

Data Warehouse Analytics Testing Sales 94

AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. To achieve this, EUROGATE designed an architecture that uses Amazon DataZone to publish specific digital twin data sets, enabling access to them with SageMaker in a separate AWS account.

IoT 101

IoT Machine Learning Metadata Data-driven 101

AWS Big Data

OCTOBER 14, 2024

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes. foundation model (FM) in Amazon Bedrock as the LLM.

Metadata 89

Metadata Data Lake Modeling Data Warehouse 89

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. A typical data pipeline for machine learning.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

Rocket-Powered Data Science

JULY 14, 2023

Now, we drill down into some of the special characteristics of data and enterprise data infrastructure that ignite analytics innovation. First, a little history – years ago, at the dawn of the big data age, there was frequent talk of the three V’s of big data (data’s three biggest challenges): volume, velocity, and variety.

Analytics 188

Analytics Big Data Strategy Enterprise 188

AWS Big Data

NOVEMBER 22, 2024

Now, with support for dbt Cloud, you can access a managed, cloud-based environment that automates and enhances your data transformation workflows. This upgrade allows you to build, test, and deploy data models in dbt with greater ease and efficiency, using all the features that dbt Cloud provides.

Data Lake 84

Data Lake Data Warehouse Cost-Benefit Data Transformation 84

AWS Big Data

DECEMBER 4, 2024

They’re taking data they’ve historically used for analytics or business reporting and putting it to work in machine learning (ML) models and AI-powered applications. Amazon SageMaker Unified Studio (Preview) solves this challenge by providing an integrated authoring experience to use all your data and tools for analytics and AI.

Data Analytics 86

Data Analytics Analytics Data Lake Data Quality 86

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Analytics Vidhya

JUNE 10, 2024

Introduction Many contemporary technologies, especially machine learning, rely heavily on labeled data.

Machine Learning 318

Machine Learning Modeling Technology Analytics 318

Analytics Vidhya

APRIL 17, 2023

The AI can connect and collaborate with multiple artificial intelligence models, such as ChatGPT and t5-base, to deliver a final result. Microsoft has recently unveiled an innovative multimodal AI-powered platform known as JARVIS.

Data Processing 302

Data Processing Testing Modeling Analytics 302

CIO Business Intelligence

NOVEMBER 1, 2024

Several co-location centers host the remainder of the firm’s workloads, and Marsh McLennans big data centers will go away once all the workloads are moved, Beswick says. Simultaneously, major decisions were made to unify the company’s data and analytics platform.

IT 122

IT Insurance Consulting Risk 122

Rocket-Powered Data Science

MARCH 20, 2023

With all the data in and around the enterprise, users would say that they have a lot of information but need more insights to assist them in producing better and more informative content. This is where we dispel an old “big data” notion (heard a decade ago) that was expressed like this: “we need our data to run at the speed of business.”

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

CIO Business Intelligence

FEBRUARY 20, 2025

Stone called outdated apps a multi-trillion-dollar problem, even after organizations have spent the past decade focused on modernizing their infrastructure to deal with big data. This allows for the extraction and integration of data into AI models without overhauling entire platforms, Erolin says.

Insurance 108

Insurance Cost-Benefit Unstructured Data Data Lake 108

O'Reilly on Data

MARCH 7, 2019

Language understanding benefits from every part of the fast-improving ABC of software: AI (freely available deep learning libraries like PyText and language models like BERT ), big data (Hadoop, Spark, and Spark NLP ), and cloud (GPU's on demand and NLP-as-a-service from all the major cloud providers). Medical embeddings.

Deep Learning 277

Deep Learning Testing Machine Learning Modeling 277

AWS Big Data

DECEMBER 4, 2024

Amazon SageMaker Unified Studio (preview) provides an integrated data and AI development environment within Amazon SageMaker. From the Unified Studio, you can collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics.

Visualization 102

Visualization Sales Data-driven Analytics 102