Dataconomy

JUNE 1, 2023

Microsoft has made good on its promise to deliver a simplified and more efficient Microsoft Fabric price model for its end-to-end platform designed for analytics and data workloads. Microsoft’s unified pricing model for the Fabric suite marks a significant advancement in the analytics and data market.

Power BI 194

Power BI Data Lakes Azure Data Silos 194

AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

AWS 90

AWS Data Governance Data Silos SQL 90

Smart Data Collective

MAY 31, 2022

It’s more than just data that provides the information necessary to make wise, data-driven decisions. It’s more than just allowing access to data warehouses that were becoming dangerously close to data silos. Data activation is about giving businesses the power to make data serve them.

ETL 142

ETL Data Silos Data Warehouse Big Data 142

Flipboard

NOVEMBER 22, 2024

It enables different business units within an organization to create, share, and govern their own data assets, promoting self-service analytics and reducing the time required to convert data experiments into production-ready applications.

Data Governance 131

Data Governance ML ML Data Lakes 131

IBM Journey to AI blog

APRIL 15, 2024

Despite heavy investments in databases and technology, many companies struggle to extract further value from their data. Data virtualization bridges this gap, allowing organizations to use their existing data sources with flexibility and efficiency for AI and analytics initiatives.

Analytics 81

Analytics Analytics Data Silos AI 81

Dataconomy

JUNE 3, 2025

This ensures that different business processes can utilize the same dimensional data, enabling a consistent understanding and analysis of information, regardless of the source. The primary purpose of conformed dimensions is to provide clarity and uniformity, which are essential for effective reporting and analytics.

ETL 91

ETL Data Warehouse Data Silos Data Lakes 91

Precisely

DECEMBER 16, 2024

AIOps, or artificial intelligence for IT operations, combines AI technologies like machine learning, natural language processing, and predictive analytics, with traditional IT operations. Tool overload can lead to inefficiencies and data silos. The difficulties faced by IT teams often boil down to three key issues: Data silos.

Artificial Intelligence 59

Artificial Intelligence Artificial Intelligence Data Silos Machine Learning 59

Smart Data Collective

SEPTEMBER 27, 2022

Now is the time for companies deploying limited tools to consider switching to cloud-based data storage and powerful product planning tools. Data silos have become one of the biggest restraints with using linear manufacturing processes. Does the platform eliminate your data silos into one accessible source of truth?

Data Silos 134

Data Silos Internet of Things Data Visualization Analytics 134

Dataconomy

FEBRUARY 13, 2025

Databricks has announced the launch of SAP Databricks , a new integration that connects the Databricks Data Intelligence Platform with the SAP Business Data Cloud. The partnership aims to help enterprises unify SAP data with other business-critical systems , improving data warehousing, AI applications, and analytics.

Data Silos 113

Data Silos AI AI Azure 113

Precisely

FEBRUARY 20, 2025

Thats where data integration comes in. Data integration breaks down data silos by giving users self-service access to enterprise data, which ensures your AI initiatives are fueled by complete, relevant, and timely information. Assessing potential challenges , like resource constraints or existing data silos.

Data Silos 69

Data Silos AI AI Data Quality 69

Precisely

OCTOBER 19, 2023

That’s what makes spatial analytics so important. Let’s explore more on what spatial analytics is, why it matters, and what you need to get started and deliver the best results? What Is Spatial Analytics? Spatial analytics is the process of conducting an analysis of data with a geographic or spatial component.

Analytics 64

Analytics Analytics Data Silos Clustering 64

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 105

AWS Analytics Analytics Machine Learning 105

Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69

Tableau

OCTOBER 7, 2024

This technology sprawl often creates data silos and presents challenges to ensuring that organizations can effectively enforce data governance while still providing trusted, real-time insights to the business.

Tableau 138

Tableau Data Quality Analytics Analytics 138

Flipboard

MAY 5, 2025

Connecting insights across data silos: LLMs can synthesize information from multiple reports and databases, delivering integrated perspectives. This system combines a user-friendly conversational interface with AI-powered relevance matching, recommendations, and analytics.

AWS 73

AWS Data Silos Database Artificial Intelligence 73

Dataconomy

MAY 26, 2025

Big data management refers to the strategies and processes involved in handling extensive volumes of structured and unstructured data to ensure high data quality and accessibility for analytics and business intelligence applications. Efficient resource management: Better data handling saves time and manpower.

Big Data 91

Big Data Big Data Apache Hadoop Data Quality 91

Alation

MARCH 21, 2023

For example, airlines have historically applied analytics to revenue management, while successful hospitality leaders make data-driven decisions around property allocation and workforce management. What is big data in the travel and tourism industry? Why is data analytics important for travel organizations?

Analytics 52

Analytics Analytics Data Silos Big Data 52

Precisely

FEBRUARY 12, 2024

For instance, telcos are early adopters of location intelligence – spatial analytics has been helping telecommunications firms by adding rich location-based context to their existing data sets for years. Despite that fact, valuable data often remains locked up in various silos across the organization.

Data Governance 64

Data Governance Analytics Analytics Machine Learning 64

ODSC - Open Data Science

APRIL 28, 2023

As critical data flows across an organization from various business applications, data silos become a big issue. The data silos, missing data, and errors make data management tedious and time-consuming, and they’re barriers to ensuring the accuracy and consistency of your data before it is usable by AI/ML.

ML 98

ML ML Data Silos Data Quality 98

Alation

MAY 2, 2023

Hospitality organizations use data analytics to unlock insights, improve operations, and maximize profits. Leveraging analytics enables companies in this space to achieve financial and operational efficiencies while delivering personalized services and offerings. What is data analytics in the hospitality industry?

Analytics 52

Analytics Analytics Data Silos Data Governance 52

Precisely

APRIL 3, 2025

A poorly managed archiving system can lead to compliance risks, data silos, and inefficiencies that slow down operations. GDPR, CCPA, SEC, HIPAA) How long must data be retained, and in what format? Can archived data support analytics, AI models, or other business initiatives?

Data Silos 64

Data Silos Analytics Analytics AI 64

IBM Journey to AI blog

OCTOBER 22, 2024

Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement. Indeed, IDC has predicted that by the end of 2024, 65% of CIOs will face pressure to adopt digital tech , such as generative AI and deep analytics.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Alation

OCTOBER 12, 2021

Enterprise data analytics enables businesses to answer questions like these. Having a data analytics strategy is a key to delivering answers to these questions and enabling data to drive the success of your business. What is Enterprise Data Analytics? Data engineering. Analytics forecasting.

Analytics 52

Analytics Analytics Data Governance DataOps 52

Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Businesses harness these innovations for real-time analytics, operational efficiency, and data democratisation, ensuring competitiveness in 2025. billion by 2030, with an impressive CAGR of 27.3%

Analytics 52

Analytics Analytics Augmented Analytics Machine Learning 52

Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. Modern businesses are increasingly leveraging analytics for a range of use cases. Analytics can help a business improve customer relationships, optimize advertising campaigns, develop new products, and much more. What is Data Analytics?

Data Governance 52

Data Governance Analytics Analytics Data Quality 52

Flipboard

MAY 14, 2025

Among these, four primary use cases have emerged as especially prominent: intelligent process automation, anomaly detection, analytics, and operational assistance. Amazon QuickSight is a comprehensive Business Intelligence (BI) environment that offers a range of advanced features for data analysis and visualization.

AWS 142

AWS AI AI Database 142

Dataconomy

APRIL 6, 2023

While data democratization has many benefits, such as improved decision-making and enhanced innovation, it also presents a number of challenges. From lack of data literacy to data silos and security concerns, there are many obstacles that organizations need to overcome in order to successfully democratize their data.

Data Governance 118

Data Governance Data Silos Data Analysis Data Analysis 118

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 101

AWS Analytics Analytics Machine Learning 101

IBM Journey to AI blog

JUNE 15, 2023

There’s no debate that the volume and variety of data is exploding and that the associated costs are rising rapidly. The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. It will leverage watsonx.ai

Data Warehouse 110

Data Warehouse Data Lakes Cloud Data Analytics 110

Dataversity

AUGUST 2, 2024

In today’s digital age, vast amounts of business data are gathered from different sources. Even when organizations strategically invest in analytics tools, they still face challenges in the form of data silos, unstructured data management, and failure of business-driven insights from tools.

Data Silos 52

Data Silos AI AI Analytics 52

IBM Journey to AI blog

MAY 9, 2024

Conversely, confidence in the accuracy and consistency of your data can minimize the risk of adverse health outcomes, rather than merely reacting to or causing them. Also, using predictive analytics can help identify trends, patterns and potential future health risks in your patients.

Data Governance 85

Data Governance Data Silos Data Quality Predictive Analytics 85

Tableau

OCTOBER 14, 2021

Having complete, accurate data in all employees’ hands and workstreams helps organizations solve business problems with the customer journey in mind—especially in rapidly changing markets. With organizations accelerating to digital business practices, data is the key to transformation.

Analytics 98

Analytics Analytics Tableau Data Governance 98

Alation

MARCH 29, 2022

The 1980s ushered in the antithesis of this version of computing — personal computing and distributed database management — but also introduced duplicated data and enterprise data silos. During the 1990s, attempts were made to tackle challenges including: Inefficient data silos. This happened for many reasons.

Business Intelligence 96

Business Intelligence Business Intelligence Data Silos Citizen Data Scientist 96

Pickl AI

APRIL 24, 2023

The primary focus of every organisation across the industry spectrums is to harness the power of data. Here comes the role of a cloud-based data analytics platform. These cloud-based platforms empower businesses to work on bulk data and process it efficiently. However, not all analytics platforms are the same.

Analytics 52

Analytics Analytics Data Analysis Data Analysis 52

AWS Machine Learning Blog

DECEMBER 3, 2024

Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems.

AWS 106

AWS Database Data Silos Data Lakes 106

Tableau

OCTOBER 14, 2021

Having complete, accurate data in all employees’ hands and workstreams helps organizations solve business problems with the customer journey in mind—especially in rapidly changing markets. With organizations accelerating to digital business practices, data is the key to transformation.

Analytics 95

Analytics Analytics Tableau Data Governance 95

IBM Journey to AI blog

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. AWS’s secure and scalable environment ensures data integrity while providing the computational power needed for advanced analytics.

AWS 95

AWS AI AI Data Warehouse 95