Smart Data Collective

APRIL 29, 2020

Dataform enables the creation of a central repository for defining data throughout an organisation, as well as discovering datasets and documenting data in a catalogue. The platform allows data quality tests to be written with alerts, and schedules that ensure data is kept current. Microsoft Azure.

Data Warehouse 97

Data Warehouse SQL Azure ETL 97

The MLOps Blog

JUNE 27, 2023

Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. Your data team can manage large-scale, structured, and unstructured data with high performance and durability.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Dataconomy

SEPTEMBER 4, 2023

Understand what insights you need to gain from your data to drive business growth and strategy. Best practices in cloud analytics are essential to maintain data quality, security, and compliance ( Image credit ) Data governance: Establish robust data governance practices to ensure data quality, security, and compliance.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Tableau

FEBRUARY 17, 2021

Enjoy significant Azure connectivity improvements to better optimize Tableau and Azure together for analytics. Microsoft Azure connectivity improvements. We are continuously working on optimizing Tableau and Azure together for analytics. Now we’ll take a deeper look at some of the biggest new features in this release.

Tableau 52

Tableau Azure Data Quality ML 52

Pickl AI

MAY 15, 2024

Data Quality and Standardization The adage “garbage in, garbage out” holds true. Inconsistent data formats, missing values, and data bias can significantly impact the success of large-scale Data Science projects. This is crucial for building trust in models and addressing potential biases.

Data Analyst 52

Data Analyst Data Scientist Data Science Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

Key components of data warehousing include: ETL Processes: ETL stands for Extract, Transform, Load. This process involves extracting data from multiple sources, transforming it into a consistent format, and loading it into the data warehouse. ETL is vital for ensuring data quality and integrity.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

AUGUST 30, 2024

Assessment Evaluate the existing data quality and structure. This step involves identifying any data cleansing or transformation needed to ensure compatibility with the target system. Assessing data quality upfront can prevent issues later in the migration process.

Data Quality 52

Data Quality Data Governance Azure Database 52

DataRobot Blog

JULY 21, 2022

The infrastructure team may want models deployed on a major cloud platform (such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure), in your on-premises data center, or both. Data aggregation such as from hourly to daily or from daily to weekly time steps may also be required.

Machine Learning 98

Machine Learning Machine Learning Data Scientist Data Quality 98

Dataversity

JUNE 2, 2021

These models allow large enterprises to tier and scale their AWS Accounts, Azure Subscriptions, and Google Projects across hundreds and thousands of cloud users and services. The deliverability of cloud governance models has improved as public cloud usage continues to grow and mature. When we first started […].

Azure 52

Azure AWS Data Governance Data Quality 52

Pickl AI

OCTOBER 15, 2024

Talend Talend is a leading open-source ETL platform that offers comprehensive solutions for data integration, data quality , and cloud data management. It supports both batch and real-time data processing , making it highly versatile. ADF allows users to create complex ETL pipelines using a drag-and-drop interface.

ETL 52

ETL Azure AWS Data Governance 52

Pickl AI

JUNE 7, 2024

Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Introduction In today’s business landscape, data integration is vital. Read Further: Azure Data Engineer Jobs.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

ODSC - Open Data Science

DECEMBER 5, 2023

Some of our most popular in-person sessions were: MLOps: Monitoring and Managing Drift: Oliver Zeigermann | Machine Learning Architect ODSC Keynote: Human-Centered AI: Peter Norvig, PhD | Engineering Director, Education Fellow | Google, Stanford Institute for Human-Centered Artificial Intelligence (HAI) The Cost of AI Compute and Why AI Clouds Will (..)

Data Science 98

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 98

Pickl AI

OCTOBER 17, 2024

Best Practices for ETL Efficiency Maximising efficiency in ETL (Extract, Transform, Load) processes is crucial for organisations seeking to harness the power of data. Implementing best practices can improve performance, reduce costs, and improve data quality. Why is ETL Important for Businesses?

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Pickl AI

DECEMBER 25, 2024

Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Techniques such as data cleansing, aggregation, and trend analysis play a critical role in ensuring data quality and relevance.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Towards AI

JUNE 25, 2024

Image generated by Gemini Spark is an open-source distributed computing framework for high-speed data processing. It is widely supported by platforms like GCP and Azure, as well as Databricks, which was founded by the creators of Spark. Let’s get started. 🤠 🔗 All code and config are available on GitHub.

ML 80

ML ML EDA Data Wrangling 80

ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Pickl AI

DECEMBER 2, 2024

Understanding these enhances insights into data management challenges and opportunities, enabling organisations to maximise the benefits derived from their data assets. Veracity Veracity refers to the trustworthiness and accuracy of the data. Value Value emphasises the importance of extracting meaningful insights from data.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Understanding these enhances insights into data management challenges and opportunities, enabling organisations to maximise the benefits derived from their data assets. Veracity Veracity refers to the trustworthiness and accuracy of the data. Value Value emphasises the importance of extracting meaningful insights from data.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making. What are the Common Challenges in Data Ingestion?

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

Alation

SEPTEMBER 30, 2022

Our ability to catalog every data asset means that we can partner with other ISVs in data quality and observability, like BigEye and Soda ; privacy, like BigID and OneTrust; access governance, like Immuta and Privacera; not to mention the core platforms, like Snowflake , Databricks , AWS , GCP, and Azure.

Data Governance 92

Data Governance Azure SQL Data Quality 92

ODSC - Open Data Science

OCTOBER 25, 2024

We’ll dive into the concept of the open data lakehouse architecture, which combines the flexibility of data lakes with the performance and atomic transaction capabilities traditionally associated with data warehouses.

AI 52

AI AI Data Scientist Data Lakes 52

Alation

NOVEMBER 11, 2021

Therefore, the question is not if a business should implement cloud data management and governance, but which framework is best for them. Whether you’re using a platform like AWS, Google Cloud, or Microsoft Azure, data governance is just as essential as it is for on-premises data. Data Quality Metrics.

Data Governance 52

Data Governance Cloud Data Data Quality Azure 52

Snorkel AI

FEBRUARY 8, 2023

The platform accommodates data from a wide range of sources, including traditional relational databases, NoSQL databases, and data stored in cloud storage platforms such as Amazon S3 or Azure Blob Storage. Users can then curate this amalgam of data and operationalize it to gain insights and value through AI.

Database 52

Database Azure AI AI 52

Snorkel AI

FEBRUARY 8, 2023

The platform accommodates data from a wide range of sources, including traditional relational databases, NoSQL databases, and data stored in cloud storage platforms such as Amazon S3 or Azure Blob Storage. Users can then curate this amalgam of data and operationalize it to gain insights and value through AI.

Database 52

Database Azure AI AI 52

Precisely

MAY 23, 2024

Whatever your approach may be, enterprise data integration has taken on strategic importance. It synthesizes all the metadata around your organization’s data assets and arranges the information into a simple, easy-to-understand format.

Data Governance 64

Data Governance ETL Data Pipeline Azure 64

Snorkel AI

OCTOBER 4, 2023

Snorkel offers enterprise-grade security in the SOC2-certified Snorkel Cloud , as well as partnerships with Google Cloud, Microsoft Azure, AWS, and other leading cloud providers. Snorkel’s data-centric approach and user-friendly platform can vastly simplify the training and deployment of credit-scoring models.

AI 64

AI AI ML ML 64

Precisely

MARCH 9, 2023

The same can be said of other leading platforms such as Databricks, Cloudera, and data lakes offered by the major cloud providers such as AWS, Google, and Microsoft Azure. Whichever platform you choose, Precisely Connect can help you integrate data from any source, including the critical mainframe systems like IBM i, z/OS, and others.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

phData

SEPTEMBER 20, 2023

Data mesh proposes a decentralized and domain-oriented model for data management to address these challenges. What are the Advantages and Disadvantages of Data Mesh? Advantages of Data Mesh Improved data quality due to domain teams having responsibility for their own data.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

Pickl AI

APRIL 9, 2025

Integration : Can it connect with existing systems like AWS, Azure, or Google Cloud? Informatica PowerCenter Informatica PowerCenter is a leading enterprise-grade ETL tool known for its robust data integration capabilities. PowerCenter is particularly favored by large organizations with extensive data integration needs.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

Pickl AI

JULY 25, 2023

Data Integration and ETL (Extract, Transform, Load) Data Engineers develop and manage data pipelines that extract data from various sources, transform it into a suitable format, and load it into the destination systems. Data Quality and Governance Ensuring data quality is a critical aspect of a Data Engineer’s role.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

JULY 12, 2024

This section explores the essential steps in preparing data for AI applications, emphasising data quality’s active role in achieving successful AI models. Importance of Data in AI Quality data is the lifeblood of AI models, directly influencing their performance and reliability.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Snorkel AI

AUGUST 24, 2023

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Data quality is essential for the success of any AI project but banks are often limited in their ability to find or label sufficient data. Natural language processing to extract key information quickly.

AI 52

AI AI Natural Language Processing Cloud Computing 52

ODSC - Open Data Science

OCTOBER 20, 2023

At the AI Expo and Demo Hall as part of ODSC West in a few weeks, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like Microsoft Azure, Hewlett Packard, Iguazio, neo4j, Tangent Works, Qwak, Cloudera, and others.

AI 52

AI AI Data Science Machine Learning 52

Snorkel AI

AUGUST 24, 2023

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Data quality is essential for the success of any AI project but banks are often limited in their ability to find or label sufficient data. Natural language processing to extract key information quickly.

AI 52

AI AI Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 24, 2023

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Data quality is essential for the success of any AI project but banks are often limited in their ability to find or label sufficient data. Natural language processing to extract key information quickly.

AI 52

AI AI Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 24, 2023

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Data quality is essential for the success of any AI project but banks are often limited in their ability to find or label sufficient data. Natural language processing to extract key information quickly.

AI 52

AI AI Artificial Intelligence Artificial Intelligence 52

Snorkel AI

OCTOBER 4, 2023

Snorkel offers enterprise-grade security in the SOC2-certified Snorkel Cloud , as well as partnerships with Google Cloud, Microsoft Azure, AWS, and other leading cloud providers. Snorkel’s data-centric approach and user-friendly platform can vastly simplify the training and deployment of credit-scoring models.

AI 59

AI AI ML ML 59