phData

FEBRUARY 14, 2023

Insurance companies often face challenges with data silos and inconsistencies among their legacy systems. To address these issues, they need a centralized and integrated data platform that serves as a single source of truth, preferably with strong data governance capabilities.

Data Governance 52

Data Governance Data Silos Predictive Analytics Data Wrangling 52

Alation

MARCH 21, 2023

While this industry has used data and analytics for a long time, many large travel organizations still struggle with data silos , which prevent them from gaining the most value from their data. What is big data in the travel and tourism industry?

Analytics 52

Analytics Analytics Data Silos Big Data 52

Precisely

FEBRUARY 12, 2024

Here are some of the key trends and challenges facing telecommunications companies today: The growth of AI and machine learning: Telecom companies use artificial intelligence and machine learning (AI/ML) for predictive analytics and network troubleshooting.

Data Governance 64

Data Governance Analytics Analytics Machine Learning 64

Ocean Protocol

APRIL 13, 2023

About Ocean Protocol Ocean Protocol is an ecosystem of open source data sharing tools for the blockchain. Ocean Protocol is spearheading the movement to unlock a New Data Economy in Web3 by breaking down data silos and opening access to high quality data.

Data Silos 52

Data Silos Machine Learning Machine Learning Predictive Analytics 52

Ocean Protocol

MARCH 7, 2023

See our Discord #events-overview channel for further details or chat with us in the dedicated #data-challenges channel. About Ocean Protocol Ocean Protocol is a decentralized data-sharing ecosystem spearheading the movement to unlock a New Data Economy, break down data silos, and open access to quality data.

Data Scientist 52

Data Scientist Data Silos Data Science Python 52

Pickl AI

DECEMBER 11, 2024

Efficiency emphasises streamlined processes to reduce redundancies and waste, maximising value from every data point. Common Challenges with Traditional Data Management Traditional data management systems often grapple with data silos, which isolate critical information across departments, hindering collaboration and transparency.

Data Silos 52

Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 52

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Ocean Protocol

APRIL 14, 2023

About Ocean Protocol Ocean Protocol is an ecosystem of open source data sharing tools for the blockchain. Ocean Protocol is spearheading the movement to unlock a New Data Economy in Web3 by breaking down data silos and opening access to high quality data.

Machine Learning 59

Machine Learning Machine Learning Data Silos Analytics 59

Dataversity

NOVEMBER 14, 2022

The COVID-19 pandemic accelerated organizations’ digital transformation efforts, regardless of whether they were ready for it or not. Now, as businesses have adjusted their plans to factor in the ongoing effects of the pandemic, digital transformation has become not just a business initiative, but one of high priority.

Data Silos 52

Data Silos Predictive Analytics Analytics Analytics 52

Pickl AI

DECEMBER 4, 2023

Implementing interoperable data platforms. Resource Allocation Improvement Optimises staff and resource allocation Balancing workload and resource availability Implementing predictive analytics for resource planning. Implementing integrated data management systems. Continuous enhancement of fraud detection algorithms.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

phData

SEPTEMBER 27, 2024

Machine Learning Layer : For predictive analytics and advanced segmentation, you might add a machine learning tool like DataRobot or H2O.ai. From Data Silos to Rivers of Information : We’re no longer content with customer data sitting in lonely silos, waiting for the next batch job to come along.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

Dataconomy

JULY 19, 2023

From predictive analytics to sentiment analysis, AI crypto projects enable data-driven decision-making in the financial realm ( Image credit ) The AGIX token is a valuable asset for anyone who is interested in the future of AI. Ocean Protocol is designed to address the challenges of data sharing and monetization.

AI 172

AI AI Artificial Intelligence Artificial Intelligence 172

Alation

MAY 2, 2023

Further, companies in the hospitality industry collect and analyze personally identifiable information (PII) that require additional security and privacy protections, like the General Data Protection Regulation (GDPR). Meanwhile, predictive analytics enable them to analyze customer market trends.

Analytics 52

Analytics Analytics Data Silos Data Governance 52

Alation

JANUARY 27, 2022

Raw data includes market research, sales data, customer transactions, and more. Analytics can identify patterns that depict risks, opportunities, and trends. And historical data can be used to inform predictive analytic models, which forecast the future. What Is the Value of Analytics?

Data Governance 52

Data Governance Analytics Analytics Data Quality 52

Alation

MAY 2, 2023

Further, companies in the hospitality industry collect and analyze personally identifiable information (PII) that require additional security and privacy protections, like the General Data Protection Regulation (GDPR). Meanwhile, predictive analytics enable them to analyze customer market trends.

Analytics 40

Analytics Analytics Data Silos Data Governance 40

Pickl AI

DECEMBER 3, 2024

Current Challenges in Data Analytics Despite the advancements in Data Analytics technologies, organisations face several challenges: Data Quality: Inconsistent or incomplete data can lead to inaccurate insights. Poor-quality data hampers decision-making and can result in significant financial losses.

Analytics 52

Analytics Analytics Data Quality AI 52