Precisely

SEPTEMBER 12, 2023

The Precisely team is excited to be part of Confluent’s Current 2023 conference, September 26 & 27. As a proud member of the Connect with Confluent program , we help organizations going through digital transformation and IT infrastructure modernization break down data silos and power their streaming data pipelines with trusted data.

Data Silos 52

Data Silos Apache Kafka Data Pipeline Data Quality 52

Precisely

FEBRUARY 10, 2023

Advanced analytics and AI/ML continue to be hot data trends in 2023. According to a recent IDC study, “executives openly articulate the need for their organizations to be more data-driven, to be ‘data companies,’ and to increase their enterprise intelligence.” Anomalous data can occur for a variety of different reasons.

DataOps 52

DataOps Data Observability ML ML 52

IBM Data Science in Practice

MARCH 8, 2023

Hidden Technical Debt in Machine Learning Systems More money, more problems — Rise of too many ML tools 2012 vs 2023 — Source: Matt Turck People often believe that money is the solution to a problem. Tools like Git and Jenkins are not suited for managing data. This is where a feature platform comes in handy. Spark, Flink, etc.)

Machine Learning 264

Machine Learning Machine Learning ML ML 264

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

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Data Quality ML ML AI 52

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

Data Quality 52

Data Quality ML ML AI 52

Precisely

JANUARY 19, 2023

In 2023 and beyond, we expect the open source trend to continue, with steady growth in the adoption of tools like Feilong, Tessla, Consolez, and Zowe. Data Integration Enterprises are betting big on analytics, and for good reason. The volume, velocity, and variety of data is growing exponentially.

AWS 52

AWS Cloud Computing Data Pipeline Big Data 52

phData

MARCH 1, 2023

This tool ​​collects, compares, analyzes, and acts on data source metadata and metrics. This allows you to perform tasks such as ensuring data quality against data sources (once or over time), compare data metrics and metadata across environments, and create/manage data pipelines for all your tables and views.

SQL 52

SQL Data Pipeline Data Quality Database 52

ODSC - Open Data Science

SEPTEMBER 20, 2023

ODSC West 2023 is just a couple of months away, and we couldn’t be more excited to be able to share our Preliminary Schedule with you! Day 1: Monday, October 30th (Bootcamp, VIP, Platinum) Day 1 of ODSC West 2023 will feature our hands-on training sessions, workshops, and tutorials and will be open to Platinum, Bootcamp, and VIP pass holders.

Data Wrangling 52

Data Wrangling Data Science Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. ETL is vital for ensuring data quality and integrity.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

AI 89

AI AI Data Quality Data Pipeline 89

Precisely

SEPTEMBER 18, 2023

Data observability is a key element of data operations (DataOps). It enables a big-picture understanding of the health of your organization’s data through continuous AI/ML-enabled monitoring – detecting anomalies throughout the data pipeline and preventing data downtime.

Data Observability 52

Data Observability Data Quality Data Pipeline DataOps 52

Alation

MAY 31, 2023

This year’s DGIQ West will host tutorials, workshops, seminars, general conference sessions, and case studies for global data leaders. DGIQ is June 5-9, 2023, at the Catamaran Resort Hotel and Spa in San Diego, just steps away from the Mission Bay beach. You can learn more about the event and register here.

Data Governance 52

Data Governance DataOps Data Pipeline Business Intelligence 52

Precisely

NOVEMBER 9, 2023

According to the 2023 Data Integrity Trends and Insights Report , data quality is the #1 barrier to achieving data integrity. And poor address quality is the top challenge preventing business leaders from effectively using location data to add context and multidimensional value to their decision-making processes.

Data Quality 64

Data Quality Data Pipeline Database 64

Precisely

MARCH 4, 2024

A striking revelation from the 2023 Gartner IT Symposium Research Super Focus Group showed that only 4% of businesses considered their data AI-ready. This big wake-up call emphasizes the urgent need for organizations to enhance their data management practices to pave the way for trusted AI applications.

AI 72

AI AI Data Quality Artificial Intelligence 72

Dataconomy

MAY 16, 2023

Key skills and qualifications for machine learning engineers include: Strong programming skills: Proficiency in programming languages such as Python, R, or Java is essential for implementing machine learning algorithms and building data pipelines.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

ODSC - Open Data Science

JUNE 19, 2023

It is the preferred operating system for data processing heavy operations for many reasons (more on this below). Around 70 percent of embedded systems use this OS and the RTOS market is expected to grow by 23 percent CAGR within the 2023–2030 forecast period, reaching a market value of over $2.5

Big Data 96

Big Data Big Data Artificial Intelligence Artificial Intelligence 96

ODSC - Open Data Science

FEBRUARY 14, 2023

Getting into Data Engineering Joe Reis | CEO | Ternary Data Perfect for those interested in getting into data engineering, this talk covers the key questions you should answer when embarking on a data engineering career. Joe Reis addresses the current economic climate in 2023 in particular.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

SEPTEMBER 3, 2024

High hopes Back in the spring of 2023—quite a long time in the artificial intelligence (AI) space—Goldman Sachs released a report estimating that the emergence of generative AI could boost global GDP by 7% annually (link resides outside IBM.com), amounting to more than an additional USD 7 trillion each year. .”

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AI AI Algorithm Artificial Intelligence 123

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Context In early 2023, Zeta’s machine learning (ML) teams shifted from traditional vertical teams to a more dynamic horizontal structure, introducing the concept of pods comprising diverse skill sets. Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly.

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AWS Machine Learning Machine Learning ML 121

AWS Machine Learning Blog

MARCH 15, 2024

In Dr. Werner Vogels’s own words at AWS re:Invent 2023 , “every second that a person has a stroke counts.” Medical data restrictions You can use machine learning (ML) to assist doctors and researchers in diagnosis tasks, thereby speeding up the process. He has worked with multiple federal agencies to advance their data and AI goals.

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IBM Journey to AI blog

JANUARY 17, 2023

A data fabric architecture elevates the value of enterprise data by providing the right data, at the right time, regardless of where it resides. To simplify the process of becoming data-driven with a data fabric, we are focusing on the four most common entry points we see with data fabric journeys.

Data Governance 58

Data Governance Data Science Data Silos AI 58

DataRobot Blog

APRIL 1, 2018

In Nick Heudecker’s session on Driving Analytics Success with Data Engineering , we learned about the rise of the data engineer role – a jack-of-all-trades data maverick who resides either in the line of business or IT. To achieve organization-wide data literacy, a new information management platform must emerge.

Analytics 40

Analytics Analytics Data Preparation Augmented Analytics 40

Pickl AI

DECEMBER 9, 2024

Introduction Big Data continues transforming industries, making it a vital asset in 2025. The global Big Data Analytics market, valued at $307.51 billion in 2023, is projected to grow to $348.21 Key challenges include data storage, processing speed, scalability, and security and compliance. What is Schema-on-read?

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

phData

AUGUST 22, 2024

Consider a data pipeline that detects its own failures, diagnoses the issue, and recommends the fix—all automatically. This is the potential of self-healing pipelines, and this blog explores how to implement them using dbt, Snowflake Cortex , and GitHub Actions. How well does it do with our data quality issues?

SQL 52

SQL Data Quality Python Data Warehouse 52

phData

DECEMBER 29, 2022

We hope you’ve had a fantastic holiday season, filled up on delicious food, and are as excited as us to kick off the 2023 calendar year. These tools include things like profiling data sources, validating data migrations, generating data pipelines and dbt sources, and bulk translating SQL.

SQL 52

SQL Database Database Administration Data Profiling 52

phData

FEBRUARY 6, 2024

One of the more common practices when developing a data pipeline is rebuilding your data for testing changes. As one of the leaders in the industry, dbt provides several options on how to execute your pipelines to increase efficiency and specifically execute what you need.

Data Pipeline 52

Data Pipeline Database SQL Data Warehouse 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. It truly is an all-in-one data lake solution. Roxie then consolidates that data and presents the results.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Iguazio

FEBRUARY 8, 2024

Continuous monitoring of resources, data, and metrics. Data Pipeline - Manages and processes various data sources. ML Pipeline - Focuses on training, validation and deployment. Application Pipeline - Manages requests and data/model validations. Collecting feedback for further tuning.

ML 52

ML ML Data Scientist AI 52

Snorkel AI

JUNE 9, 2023

“You need to find a place to park your data. It needs to be optimized for the type of data and the format of the data you have,” he said. By optimizing every part of the data pipeline, he said, “You will, as a result, get your models to market faster.” Catch the sessions you missed!

AI 52

AI AI Data Scientist Machine Learning 52

Snorkel AI

JUNE 9, 2023

“You need to find a place to park your data. It needs to be optimized for the type of data and the format of the data you have,” he said. By optimizing every part of the data pipeline, he said, “You will, as a result, get your models to market faster.” Catch the sessions you missed!

AI 52

AI AI Data Scientist Machine Learning 52

Flipboard

MARCH 21, 2025

Amazon SageMaker Catalog serves as a central repository hub to store both technical and business catalog information of the data product. To establish trust between the data producers and data consumers, SageMaker Catalog also integrates the data quality metrics and data lineage events to track and drive transparency in data pipelines.

SQL 132

SQL Data Analyst Data Warehouse AWS 132

ODSC - Open Data Science

APRIL 26, 2023

Data Engineer Data engineers are the authors of the infrastructure that stores, processes, and manages the large volumes of data an organization has. The main aspect of their profession is the building and maintenance of data pipelines, which allow for data to move between sources. Well then, you’re in luck.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

phData

JULY 18, 2023

The Ultimate Modern Data Stack Migration Guide phData Marketing July 18, 2023 This guide was co-written by a team of data experts, including Dakota Kelley, Ahmad Aburia, Sam Hall, and Sunny Yan. Imagine a world where all of your data is organized, easily accessible, and routinely leveraged to drive impactful outcomes.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

phData

SEPTEMBER 27, 2024

In transitional modeling, we’d add new atoms: Subject: Customer#1234 Predicate: hasEmailAddress Object: "john.new@example.com" Timestamp: 2023-07-24T10:00:00Z The old email address atoms are still there, giving us a complete history of how to contact John. Both persistent staging and data lakes involve storing large amounts of raw data.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52

Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. The reason is that most teams do not have access to a robust data ecosystem for ML development.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. The reason is that most teams do not have access to a robust data ecosystem for ML development.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

The MLOps Blog

MARCH 21, 2023

Olalekan said that most of the random people they talked to initially wanted a platform to handle data quality better, but after the survey, he found out that this was the fifth most crucial need. And when the platform automates the entire process, it’ll likely produce and deploy a bad-quality model.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69