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 132

Data Governance ML ML Data Lakes 132

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

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

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

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

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 95

AWS Analytics Analytics Machine Learning 95

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 52

Data Silos Analytics Analytics AI 52

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

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

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

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

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

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

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 Data Warehouse AI AI 95

IBM Journey to AI blog

OCTOBER 18, 2024

Strong integration capabilities ensure smooth data flow between departments, eliminating data silos. IBM Planning Analytics, powered by its in-memory TM1 engine, stands out for its scalability, integrated AI features and transparent pricing. Flexibility is key.

Data Silos 101

Data Silos Analytics Analytics AI 101

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 90

AWS Analytics Analytics Machine Learning 90

Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Analytics data catalog. Data quality and lineage. Augmented analytics.

Tableau 102

Tableau Data Quality Analytics Analytics 102

IBM Data Science in Practice

NOVEMBER 28, 2022

As organizations steer their business strategies to become data-driven decision-making organizations, data and analytics are more crucial than ever before. How can organizations get a holistic view of data when it’s distributed across data silos? Implementing a data fabric architecture is the answer.

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

Tableau

SEPTEMBER 14, 2021

And data-driven decision making, defined as taking action and influencing innovation with data and analytics, played a critical role in business response to the pandemic. Moving ahead, data-driven decisions will outweigh gut decision-making as normal operations resume. “A Data in isolation isn’t useful.

Tableau 105

Tableau Analytics Analytics Data Silos 105

Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Analytics data catalog. Data quality and lineage. Augmented analytics.

Tableau 98

Tableau Data Quality Analytics Analytics 98

IBM Journey to AI blog

JANUARY 30, 2024

Besides paying for unnecessary or forgotten workloads, overprovisioning can also increase the multicloud attack surface, making it more vulnerable to data breaches or cyberattacks. Data silos: With data spread across multiple clouds and platforms, an organization risks creating data silos.

Cloud Computing 115

Cloud Computing Data Silos Azure AWS 115

Tableau

SEPTEMBER 14, 2021

And data-driven decision making, defined as taking action and influencing innovation with data and analytics, played a critical role in business response to the pandemic. Moving ahead, data-driven decisions will outweigh gut decision-making as normal operations resume. “A Data in isolation isn’t useful.

Tableau 98

Tableau Analytics Analytics Data Silos 98

Dataconomy

SEPTEMBER 23, 2024

For instance, companies can use data to recommend products based on past purchases or browsing history. Optimizing marketing efforts: Data activation enables merging data from different sources, such as CRM systems, analytics tools, and marketing automation software.

Data Lakes 103

Data Lakes Data Silos Analytics Analytics 103

Dataconomy

APRIL 27, 2023

OLTP systems require both regular full backups and constant incremental backups to ensure that data can be quickly restored in the event of a problem. OLTP vs OLAP OLTP and online analytical processing ( OLAP ) are two distinct online data processing systems, although they share similar acronyms.

Database 159

Database Data Scientist Data Mining Data Mining 159

IBM Journey to AI blog

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

Data Warehouse 92

Data Warehouse AWS AI AI 92

Precisely

JANUARY 17, 2023

Technology helped to bridge the gap, as AI, machine learning, and data analytics drove smarter decisions, and automation paved the way for greater efficiency. IoT devices provide data feeds from smart machinery, monitoring the location and condition of shipping containers and reporting on the health and safety of workers in the field.

Data Quality 97

Data Quality Machine Learning Machine Learning Data Silos 97

IBM Journey to AI blog

JANUARY 23, 2023

Ensure data quality Regularly check your data for accuracy and completeness. Break down data silos Data silos are the bane of any data governance program. Put processes in place to fix any issues that you find. Remember: garbage in, garbage out.

Data Governance 74

Data Governance Data Silos Data Quality AI 74

phData

APRIL 18, 2023

This is due to a fragmented ecosystem of data silos, a lack of real-time fraud detection capabilities, and manual or delayed customer analytics, which results in many false positives. Snowflake Marketplace offers data from leading industry providers such as Axiom, S&P Global, and FactSet.

Data Silos 52

Data Silos ETL Clustering Analytics 52

Smart Data Collective

JUNE 3, 2019

Big Data’s most effective strategies identify business requirements first, and then leverage existing infrastructure, data sources and analytical solutions to support the business opportunity. Customer-focused analysis dominates Big Data initiatives. The industry is adopting a pragmatic, results-focused approach.

Big Data 85

Big Data Big Data Data Silos AI 85