Dataversity

AUGUST 27, 2024

While the cloud promises unparalleled scalability and flexibility, navigating the transition can be complex. Here’s a straightforward guide to overcoming key challenges and making the most of cloud computing.

Cloud Computing 52

Cloud Computing Data Governance Data Quality 52

Precisely

APRIL 6, 2023

Building a Trusted Single View of Critical Data Most organizations are at least somewhat aware of problems with data quality and accuracy. As they mature, technology teams tend to shift from a narrow focus on data quality to a big-picture aspiration to build trust in their data. Real-time data is the goal.

Data Quality 52

Data Quality Data Pipeline Analytics Analytics 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 Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

JUNE 19, 2023

These technologies include the following: Data governance and management  — It is crucial to have a solid data management system and governance practices to ensure data accuracy, consistency, and security. It is also important to establish data quality standards and strict access controls.

Big Data 96

Big Data Big Data Artificial Intelligence Artificial Intelligence 96

Precisely

SEPTEMBER 5, 2023

Data is pivotal for the success of business operations. With cloud computing, the capacity to extract value from data is greater than ever. As this realization grows, businesses are shifting their investments from hardware to technologies that optimize data assets. Do you have high data quality ?

Data Governance 52

Data Governance Data Quality Cloud Computing Data Classification 52

Pickl AI

OCTOBER 6, 2024

This phase is crucial for enhancing data quality and preparing it for analysis. Transformation involves various activities that help convert raw data into a format suitable for reporting and analytics. Normalisation: Standardising data formats and structures, ensuring consistency across various data sources.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

Precisely

JANUARY 19, 2023

Yet mainframes weren’t designed to integrate easily with modern distributed computing platforms. Cloud computing, object-oriented programming, open source software, and microservices came about long after mainframes had established themselves as a mature and highly dependable platform for business applications.

AWS 52

AWS Cloud Computing Data Pipeline Big Data 52

Alation

DECEMBER 14, 2021

That confusion is enough to make some decision-makers procrastinate far longer than they should in migrating to the cloud! But by partnering with a professional consultant in data quality management systems, forward-thinking enterprises gain a significant competitive edge over their competitors. What is cloud-native?

Cloud Computing 52

Cloud Computing Azure AWS Data Quality 52

IBM Journey to AI blog

DECEMBER 7, 2023

Security and compliance : Ensuring data security and compliance with regulatory requirements in the cloud environment can be complex. Skills and expertise : Transitioning to cloud-based OLAP may require specialized skills and expertise in cloud computing and OLAP technologies.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

IBM Journey to AI blog

DECEMBER 20, 2023

It will also determine the talent the organization needs to develop, attract or retain with relevant skills in data science, machine learning (ML) and AI development. It will also guide the procurement of the necessary hardware, software and cloud computing resources to ensure effective AI implementation.

AI 89

AI AI Artificial Intelligence Artificial Intelligence 89

phData

JUNE 27, 2023

The modern data stack (MDS) has seen massive changes over the past few decades, fueled by technological advances and new platforms. As a result, we are presented with specialized data platforms, databases, and warehouses. All of which have a specific role used to collect, store, process, and analyze data.

SQL 52

SQL Database Data Quality Data Warehouse 52

Pickl AI

NOVEMBER 28, 2024

Familiarity with cloud computing tools supports scalable model deployment. Knowledge of Cloud Computing and Big Data Tools As complex Machine Learning (ML) models grow, robust infrastructure for large datasets and intensive computations becomes increasingly important.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

DECEMBER 16, 2024

Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs) accelerate the training of large models by efficiently processing vast amounts of data. For scalability and cost efficiency, organisations often leverage cloud computing platforms, which provide on-demand access to these powerful resources.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm Data Quality 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. Precisely helps enterprises manage the integrity of their data.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Big Data 59

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

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 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 Artificial Intelligence 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 Artificial Intelligence Natural Language Processing 52

DataSeries

OCTOBER 13, 2024

Data-Centric AI Data-centric AI is a shift from model and code-centric ways to focus on data quality and availability to develop better AI systems. The Final Verdict The notion that jobs for data scientists will disappear by 2030 is somewhat misleading.

Data Science 40

Data Science Data Scientist ML ML 40

Pickl AI

APRIL 9, 2023

The cloud analytics segment is showing a maximum growth rate of 23% As per the Drawing from Dresner’s 2020 report on business intelligence and cloud computing, around 54% believe implementing Cloud Business Intelligence tools is critical. In addition, it cannot handle large volumes of data sources. billion by 2028.

Power BI 52

Power BI Business Intelligence Business Intelligence Cloud Computing 52

Dataconomy

MARCH 28, 2023

Implementing robust security measures:  Implementing robust security measures, such as encryption, firewalls, and intrusion detection systems, can help protect sensitive data. Leveraging cloud computing:  Cloud computing can provide scalable and cost-effective data storage and processing solutions for IoT ecosystems.

Data Science 70

Data Science Internet of Things Analytics Analytics 70

Dataconomy

MARCH 28, 2023

Implementing robust security measures:  Implementing robust security measures, such as encryption, firewalls, and intrusion detection systems, can help protect sensitive data. Leveraging cloud computing:  Cloud computing can provide scalable and cost-effective data storage and processing solutions for IoT ecosystems.

Data Science 70

Data Science Internet of Things Analytics Analytics 70

AWS Machine Learning Blog

NOVEMBER 16, 2023

Data Management – Efficient data management is crucial for AI/ML platforms. Regulations in the healthcare industry call for especially rigorous data governance. It should include features like data versioning, data lineage, data governance, and data quality assurance to ensure accurate and reliable results.

AWS 112

AWS ML ML AI 112

Pickl AI

SEPTEMBER 3, 2024

Data Quality and Availability The performance of ANNs heavily relies on the quality and quantity of the training data. Insufficient or biased data can lead to inaccurate predictions and reinforce existing biases. Solution: Leveraging cloud computing and GPU acceleration can help expedite the training process.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning Deep Learning 52

Pickl AI

AUGUST 1, 2024

MXNet: An efficient and flexible Deep Learning framework that supports multiple programming languages and is particularly well-suited for cloud computing. Data Quality and Quantity Deep Learning models require large amounts of high-quality, labelled training data to learn effectively.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Heartbeat

OCTOBER 25, 2023

The following are some critical challenges in the field: a) Data Integration: With the advent of high-throughput technologies, enormous volumes of biological data are being generated from diverse sources.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Algorithm 52

Dataversity

MARCH 14, 2024

Many companies hesitate to migrate to the cloud for a variety of valid reasons. However, these migration concerns are often based on misconceptions that keep companies from realizing the financial and operational benefits of the cloud.

Data Governance 69

Data Governance Data Quality Cloud Computing 69

Dataversity

DECEMBER 23, 2022

Ask any data or security professional and chances are they will say that the growing number of global threats combined with the increasing demand by consumers to understand how their data is being used, stored, and accessed has made their job extremely stressful.

Data Quality 52

Data Quality Cloud Computing 52

Dataversity

JUNE 20, 2022

Globally, organizations are churning out data in massive volumes for a plethora of reasons. Data enables organizations to speed up innovation, take business-critical decisions confidently, get deep consumer insights, and use all that information to stay ahead of their competitors. However, where does all that data go?

Data Governance 52

Data Governance Data Quality Cloud Computing 52

AWS Machine Learning Blog

JANUARY 26, 2024

This is backed by our deep set of over 300 cloud security tools and the trust of our millions of customers, including the most security-sensitive organizations like government, healthcare, and financial services.

AWS 137

AWS ML ML AI 137

BAIR

APRIL 3, 2023

ChatGPT Distillation Data Public User-Shared Dialogues with ChatGPT (ShareGPT) Around 60K dialogues shared by users on ShareGPT were collected using public APIs. To maintain data quality, we deduplicated on the user-query level and removed any non-English conversations. This leaves approximately 30K examples.

Cloud Computing 145

Cloud Computing Artificial Intelligence Artificial Intelligence Data Quality 145

Dataconomy

APRIL 4, 2023

Anything as a Service is a cloud computing model that refers to the delivery of various services, applications, and resources over the internet. XaaS enables businesses to access a wide range of services and solutions by providing a flexible, cost-effective, and scalable model for cloud computing.

Cloud Computing 79

Cloud Computing Internet of Things Azure Artificial Intelligence 79

Dataconomy

APRIL 4, 2023

Anything as a Service is a cloud computing model that refers to the delivery of various services, applications, and resources over the internet. XaaS enables businesses to access a wide range of services and solutions by providing a flexible, cost-effective, and scalable model for cloud computing.

Cloud Computing 70

Cloud Computing Internet of Things Azure Artificial Intelligence 70

Pickl AI

MAY 15, 2024

Scalable cloud platforms and distributed processing frameworks are crucial for handling massive datasets and computationally intensive tasks. Data Quality and Standardization The adage “garbage in, garbage out” holds true. Familiarize yourself with their services for data storage, processing, and model deployment.

Data Analyst 52

Data Analyst Data Scientist Data Science Machine Learning 52

Precisely

FEBRUARY 10, 2023

According to the IDC report, “organizations that have implemented DataOps have seen a 40% reduction in the number of data and application exceptions or errors and a 49% improvement in the ability to deliver data projects on time.”

DataOps 52

DataOps Data Observability ML ML 52

Alation

OCTOBER 12, 2021

Spotlight friction areas and bottlenecks for data consumers (and build a solution). Create a blueprint of data architecture to find inconsistent definitions. Build a roadmap for future data and analytics projects, like cloud computing. Evaluate and monitor data quality. Set consistent data policies.

Analytics 52

Analytics Analytics Data Governance DataOps 52

Alation

FEBRUARY 13, 2020

John : One thing we’ve observed, and I want to get your reaction to this, is that safe cloud computing. You see scale, obviously data science work in the cloud. Now, there’s multiple clouds. Multi-clouds is a big trend, but also the validation that it’s not just all cloud anymore.

Algorithm 52

Algorithm Data Quality Analytics Analytics 52