Cloudera

APRIL 22, 2022

Communications service providers (CSPs) are rethinking their approach to enterprise services in the era of advanced wireless connectivity and 5G networks, as well as with the continuing maturity of fibre and Software-Defined Wide Area Network (SD-WAN) portfolios. . Location-specific data.

Enterprise 134

Enterprise Internet of Things Manufacturing Management 134

Dataiku

JUNE 27, 2024

Data collection is not new to the enterprise and serves as the foundation for all analytics across organizations. However, collecting information about someone’s gender, race, religion, or sexual orientation has a storied history around the world. Many ask, “Why do you need this data?

Data Collection 64

Data Collection Reporting Enterprise Analytics 64

CIO Business Intelligence

FEBRUARY 20, 2025

The data retention issue is a big challenge because internally collected data drives many AI initiatives, Klingbeil says. With updated data collection capabilities, companies could find a treasure trove of data that their AI projects could feed on. of their IT budgets on tech debt at that time.

Insurance 108

Insurance Cost-Benefit Unstructured Data Data Lake 108

CIO Business Intelligence

NOVEMBER 19, 2024

The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data. The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows.

Management 116

Management Unstructured Data Deep Learning Metadata 116

CIO Business Intelligence

NOVEMBER 1, 2023

One of the first use cases of artificial intelligence in many companies, including both Michelin and Albemarle, was predictive maintenance, which at its most basic level is an algorithm trained on data collected by sensors. To fill the gap, many companies complement the real data with synthetic data.

Enterprise 131

Enterprise Digital Transformation Modeling Interactive 131

O'Reilly on Data

MAY 14, 2020

The foundation of any data product consists of “solid data infrastructure, including data collection, data storage, data pipelines, data preparation, and traditional analytics.” These companies often have access to a lot of data at the beginning of the development cycle—also unlike consumer products.

Management 364

Management Experimentation B2B Machine Learning 364

Rocket-Powered Data Science

MARCH 10, 2020

“Shocking Amount of Data” An excerpt from my chapter in the book: “We are fully engulfed in the era of massive data collection. All those data represent the most critical and valuable strategic assets of modern organizations that are undergoing digital disruption and digital transformation.

Data Collection 248

Data Collection Digital Transformation Big Data Forecasting 248

Cloudera

JUNE 2, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. What is the modern data stack? In the modern data stack, there is a diverse set of destinations where data needs to be delivered.

Enterprise 104

Enterprise Data Lake Data Collection Data-driven 104

Rocket-Powered Data Science

MARCH 19, 2021

The dynamic changes of the business requirements and value propositions around data analytics have been increasingly intense in depth (in the number of applications in each business unit) and in breadth (in the enterprise-wide scope of applications in all business units in all sectors).

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

Rocket-Powered Data Science

MAY 21, 2024

Pure Storage empowers enterprise AI with advanced data storage technologies and validated reference architectures for emerging generative AI use cases. Summary AI devours data. I believe that the time, place, and season for artificial intelligence (AI) data platforms have arrived. AI Then and AI Now!

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

FineReport

FEBRUARY 28, 2020

What Is Enterprise Reporting? Enterprise reporting is a process of extracting, processing, organizing, analyzing, and displaying data in the companies. It uses enterprise reporting tools to organize data into charts, tables, widgets, or other visualizations. Common Problems With Enterprise Reporting.

Reporting 96

Reporting Enterprise Visualization Business Intelligence 96

Sisense

JULY 6, 2020

Employing Enterprise Data Management (EDM). What is enterprise data management? Companies looking to do more with data and insights need an effective EDM setup in place. The team in charge of your company’s EDM is focused on a set of processes, practices, and activities across the entire data lineage process.

Enterprise 98

Enterprise Management Data Architecture Data-driven 98

DataRobot Blog

MARCH 8, 2023

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

Enterprise 105

Enterprise Experimentation Machine Learning Data Science 105

Rocket-Powered Data Science

JUNE 17, 2022

.’ Observability delivers actionable insights, context-enriched data sets, early warning alert generation, root cause visibility, active performance monitoring, predictive and prescriptive incident management, real-time operational deviation detection (6-Sigma never had it so good!), Reference ) Splunk Enterprise 9.0

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

Jet Global

APRIL 2, 2019

Artificial Intelligence is coming for the enterprise. Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. The road to AI supremacy in enterprise business starts with investment in an area most businesses might not think to look at first.

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

O'Reilly on Data

JUNE 18, 2019

Even with advances in building robust models, the reality is that noisy data and incomplete data remain the biggest hurdles to effective end-to-end solutions. The problem is even more magnified in the case of structured enterprise data. These data sets are often siloed, incomplete, and extremely sparse.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

CIO Business Intelligence

JULY 13, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. What is the modern data stack? In the modern data stack, there is a diverse set of destinations where data needs to be delivered.

Enterprise 88

Enterprise Data Lake Data Collection Data-driven 88

David Menninger's Analyst Perspectives

SEPTEMBER 24, 2024

As I’ve written recently , artificial intelligence governance is a concern for many enterprises. In our recent ISG Market Lens study on generative AI, 39% of participants cited data privacy and security among the biggest inhibitors to adopting AI. Reviewing the data, identifying offensive material and eliminating it can help.

Testing 173

Testing Modeling Enterprise Risk 173

Rocket-Powered Data Science

JULY 13, 2023

Data is more than just another digital asset of the modern enterprise. As illustrated here, you can practically see the speed of business questions accelerating across the whole enterprise. Access to data has done that. It is an essential asset. And it is now a fundamental feature of any successful organization.

Analytics 167

Analytics Machine Learning Data Science Data Collection 167

O'Reilly on Data

OCTOBER 16, 2018

Create a coherent BI strategy that aligns data collection and analytics with the general business strategy. They recognize the instrumental role data plays in creating value and see information as the lifeblood of the organization. That’s why decision-makers consider business intelligence their top technology priority.

Business Intelligence 231

Business Intelligence Data Science Descriptive Analytics Data Collection 231

IBM Big Data Hub

FEBRUARY 23, 2024

Enterprises can use NLU to offer personalized experiences for their users at scale and meet customer needs without human intervention. It signifies a shift in human-digital interaction, offering enterprises innovative ways to engage with their audience, optimize operations, and further personalize their customer experience.

Enterprise 95

Enterprise Interactive Data-driven Key Performance Indicator 95

O'Reilly on Data

MARCH 31, 2020

The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies. For enterprise products , requirements often come from a small number of vocal customers with large accounts. If you can’t walk, you’re unlikely to run.

Management 363

Management Machine Learning Experimentation Metrics 363

Smart Data Collective

MAY 16, 2022

Data management systems provide a systematic approach to information storage and retrieval and help in streamlining the process of data collection, analysis, reporting, and dissemination. It also helps in providing visibility to data and thus enables the users to make informed decisions.

Management 136

Management Data mining Data Warehouse Data Collection 136

Cloudera

DECEMBER 6, 2024

The AI Forecast: Data and AI in the Cloud Era , sponsored by Cloudera, aims to take an objective look at the impact of AI on business, industry, and the world at large. Data collectives are going to merge over time, and industry value chains will consolidate and share information. It’s not direct competitors.

Manufacturing 82

Manufacturing Forecasting Metadata Data Processing 82

Smart Data Collective

SEPTEMBER 30, 2022

An enterprise cannot just become successful based on the ideas or business plans of its creator. Before your enterprise can become successful, you will need to fund it. Unfortunately, the amount of money needed to finance an enterprise can sometimes be larger than what you can bear. This is especially true for cloud startups.

Finance 124

Finance Data Processing Enterprise Data Collection 124

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

Cloudera

JANUARY 20, 2021

The six steps are: Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a brick and mortar retail store). Data Enrichment – data pipeline processing, aggregation & management to ready the data for further refinement.

Digital Transformation 110

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 110

CIO Business Intelligence

SEPTEMBER 5, 2024

Oracle is an enterprise software vendor based in Austin, Texas. Oracle’s $115 million privacy settlement could change industry data collection methods July 23, 2024: In addition to the payment, Oracle has agreed to stop tracking users in various ways. Oracle makes its pitch for the enterprise cloud. Should CIOs listen?

Enterprise 119

Enterprise Software Manufacturing Data-driven 119

Smart Data Collective

DECEMBER 9, 2021

Businesses already have a wealth of data but understanding your business will help you identify a data need – what kind of data your business needs to collect and if it collects too much or too little of certain data. Collecting too much data would be overwhelming and too little – inefficient.

Big Data 142

Big Data Data-driven Key Performance Indicator Testing 142

Smart Data Collective

SEPTEMBER 13, 2021

Many organizations and enterprises are constantly under threat of a cyber attack. Although data may be lost in a hacking incident, it can also be due to other intentional or accidental reasons. For example, you cannot rule out physical data theft, human error, computer viruses, faulty hardware, power failure, and natural disasters.

Risk 143

Risk Strategy Enterprise Finance 143

Smart Data Collective

MARCH 2, 2022

No-Code Platforms Are the Future of Data Science and AI. There is a significant shift in tools, processes, and skills being used in the enterprise. As a result, low-code/no-code next-gen technologies are starting to reach the enterprise. Dubbed a “No Code Startup for Data Scientists”, Obviously AI received $4.7

Data Science 139

Data Science Enterprise Insurance Digital Transformation 139

Smart Data Collective

APRIL 8, 2020

sThe recent years have seen a tremendous surge in data generation levels , characterized by the dramatic digital transformation occurring in myriad enterprises across the industrial landscape. The amount of data being generated globally is increasing at rapid rates. Big data and data warehousing.

Technology 144

Technology Data Warehouse Big Data Machine Learning 144

CIO Business Intelligence

OCTOBER 2, 2024

And Doug Shannon, automation and AI practitioner, and Gartner peer community ambassador, says the vast majority of enterprises are now focused on two categories of use cases that are most likely to deliver positive ROI. Classifiers are provided in the toolkits to allow enterprises to set thresholds. “We

Management 141

Management Data Governance Cost-Benefit Structured Data 141

erwin

JULY 26, 2019

Enterprise architecture (EA) isn’t dead, you’re just using it wrong. I’ll let you in on a little secret: the rumor of enterprise architecture’s demise has been greatly exaggerated. However, the truth for many of today’s fast-moving businesses is that enterprise architecture fails. Don’t Put Enterprise Architecture in a Corner.

Digital Transformation 106

Digital Transformation Strategy Enterprise Business Intelligence 106

O'Reilly on Data

NOVEMBER 13, 2018

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Let’s begin by looking at the state of adoption.

Machine Learning 277

Machine Learning Risk Management Statistics 277

Smart Data Collective

MAY 28, 2021

Data security and data collection are both much more important than ever. Every organization needs to invest in the right big data tools to make sure that they collect the right data and protect it from cybercriminals. One tool that many data-driven organizations have started using is Microsoft Azure.

Data-driven 139

Data-driven Cost-Benefit Big Data Data Processing 139

datapine

JANUARY 6, 2022

In fact, a Digital Universe study found that the total data supply in 2012 was 2.8 Based on that amount of data alone, it is clear the calling card of any successful enterprise in today’s global world will be the ability to analyze complex data, produce actionable insights and adapt to new market needs… all at the speed of thought.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246