CIO Business Intelligence

APRIL 11, 2024

Oracle Cloud Infrastructure is now capable of hosting a full range of traditional and modern IT workloads, and for many enterprise customers, Oracle is a proven vendor,” says David Wright, vice president of research for cloud infrastructure strategies at research firm Gartner. The inherent risk is trust.

Enterprise 124

Enterprise IT Data Processing Strategy 124

Laminar Security

DECEMBER 1, 2023

DSPM is a term coined by Gartner to describe solutions that focus on discovering, classifying, and protecting sensitive data in cloud environments. DSPM solutions help organizations achieve data security compliance, reduce data breach risks, optimize cloud costs, and improve data quality, all while enabling data-driven innovation.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

IBM Big Data Hub

MAY 8, 2023

Should the parameters of an algorithm be leaked, a third party may be able to copy the model, causing economic and intellectual property loss to the owner of the model. This is to ensure the AI model captures data inputs and usage patterns, required validations and testing cycles, and expected outputs.

Insurance 69

Insurance Risk Testing Data Quality 69

datapine

SEPTEMBER 27, 2022

Some of these ‘structures’ may include putting all the information; for instance, a structure could be about cars, placing them into tables that consist of makes, models, year of manufacture, and color. With a MySQL dashboard builder , for example, you can connect all the data with a few clicks. Viescas, Douglas J.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. Across the industry, the pandemic caused a huge breakdown in model performance due to the change in macroeconomic conditions and government stimulus packages. Mental health of employees is a critical area to monitor .

Risk 101

Risk Optimization Management Insurance 101

erwin

APRIL 16, 2021

Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations. Click here to read our success story on how E.ON

Data Governance 128

Data Governance Metadata Cost-Benefit Digital Transformation 128

CIO Business Intelligence

JUNE 2, 2022

HPC5’s performance level enables sophisticated in-house algorithms to process subsoil data, as well as geophysical and seismic information from around the world. For optimizing existing resources, Eni uses HPC5 to model, study, and ultimately improve refinement operations. .

Informatics 98

Informatics Modeling Testing Technology 98

IBM Big Data Hub

DECEMBER 20, 2023

Algorithms: Algorithms are the rules or instructions that enable machines to learn, analyze data and make decisions. A model represents what was learned by a machine learning algorithm. Determine who will deploy algorithms and design, develop and validate models, as expertise is needed to effectively manage these tasks.

Strategy 74

Strategy Business Objectives Cost-Benefit Consulting 74

CIO Business Intelligence

MAY 20, 2022

National Grid is a big Microsoft Azure cloud customer due to its secure, proprietary nature, says Karaboutis, and is using a bevy of leading-edge tools, from Snowflake, Azure, and Matallion ETL for data tooling, Informatica for data quality, Reltio for master data management, and Blue Prism for RPA, to name a few.

IT 105

IT Digital Transformation Internet of Things Data Architecture 105

Timo Elliott

JANUARY 4, 2021

I recently participated in a web seminar on the Art and Science of FP&A Storytelling, hosted by the founder and CEO of FP&A Research Larysa Melnychuk along with other guests Pasquale della Puca , part of the global finance team at Beckman Coulter and Angelica Ancira , Global Digital Planning Lead at PepsiCo. The key takeaways.

Dashboards 139

Dashboards Visualization Data-driven Forecasting 139

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. For machine learning systems used in consumer internet companies, models are often continuously retrained many times a day using billions of entirely new input-output pairs.

Management 327

Management Machine Learning Experimentation Metrics 327

CIO Business Intelligence

JANUARY 4, 2023

Recently members of our community came together for a roundtable discussion, hosted by Dell Technologies, about trends, trials, and all the excitement around what’s next. Of course, data center challenges are also driving demand for these alternatives.

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

Ontotext

SEPTEMBER 15, 2020

There must be a representation of the low-level technical and operational metadata as well as the ‘real world’ metadata of the business model or ontologies. The multiple and varying ‘views’ of the data are now possible without modifying the data at its source or the host system.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

DataKitchen

FEBRUARY 21, 2023

Overview of Gartner’s data engineering enhancements article To set the stage for Gartner’s recommendations, let’s give an example of a new Data Engineering Manager, Marcus, who faces a whole host of challenges to succeed in his new role: Marcus has a problem.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

Ontotext

DECEMBER 1, 2023

Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises. from Q&A with Tim Berners-Lee ) Finally, Sumit highlighted the importance of knowledge graphs to advance semantic data architecture models that allow unified data access and empower flexible data integration.

Metadata 78

Metadata Sales Consulting Enterprise 78

Alation

MAY 19, 2022

Never underestimate the power of small data. Think about what data you can create. Synthetic data is growing in popularity as a tool for data scientists. This is data that’s artificially produced to mimic and model real events: It retains the structure of the original data but is not the same as real data.

Metadata 52

Metadata Data Analytics Analytics Data Governance 52

CIO Business Intelligence

APRIL 25, 2022

It culminates with a capstone project that requires creating a machine learning model. Data Science Dojo. Due to the short nature of the course, it’s tailored to those already in the industry who want to learn more about data science or brush up on the latest skills. Switchup rating: 5.0 (out Cost: $1,099.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault.

Enterprise 87

Enterprise Data Warehouse Snapshot Cost-Benefit 87

datapine

AUGUST 7, 2019

If you’re part of a growing SaaS company and are looking to accelerate your success, leveraging the power of data is the way to gain a real competitive edge. A SaaS dashboard is a powerful business intelligence tool that offers a host of benefits for ambitious tech businesses. That’s where SaaS dashboards enter the fold.

Dashboards 168

Dashboards Management KPI Cost-Benefit 168

Domino Data Lab

OCTOBER 1, 2020

Combining the power of Domino Data Labs with Okera, your data scientists only get access to the columns, rows, and cells allowed, easily removing or redacting sensitive data such as PII and PHI not relevant to training models. So what does this look like? client('s3') obj = s3.get_object(Bucket='clinical-trials',

Enterprise 105

Enterprise Metadata Cost-Benefit Data Processing 105

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

Testing 300

Testing Machine Learning Consulting Data Quality 300

FineReport

APRIL 26, 2023

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. E-commerce giants like Alibaba and Amazon extensively use big data to understand the market. Unlike traditional databases, processing large data volumes can be quite challenging. Easy implementation.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. This post explains how you can extend the governance capabilities of Amazon DataZone to data assets hosted in relational databases based on MySQL, PostgreSQL, Oracle or SQL Server engines.

Metadata 77

Metadata Data Lake Data Processing Data-driven 77

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Enterprise 74

Enterprise Data Integration Data Quality Contextual Data 74

Cloudera

OCTOBER 1, 2022

Adam Wood, director of data governance and data quality at a financial services institution (FSI). Sam Charrington, founder and host of the TWIML AI Podcast. Sam Charrington, founder and host of the TWIML AI Podcast. Common data governance challenges for global enterprises: Setting up a multidisciplinary data team.

Data Governance 76

Data Governance Strategy Enterprise Machine Learning 76

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. The reality of LLMs and other “narrow” AI technologies is that none of them is turn-key.

Insurance 84

Insurance Risk Data-driven Finance 84

CIO Business Intelligence

FEBRUARY 28, 2024

However, getting into the more difficult types of implementations — the fine-tuned models, vector databases to provide context and up-to-date information to the AI systems, and APIs to integrate gen AI into workflows — is where problems might crop up. That’s fine, but language models are great for language. They need stability.

IT 131

IT Consulting Modeling Enterprise 131

IBM Big Data Hub

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. The explosion of data volume in different formats and locations and the pressure to scale AI looms as a daunting task for those responsible for deploying AI.

Cost-Benefit 70

Cost-Benefit Data Integration Data Architecture Manufacturing 70

CIO Business Intelligence

JUNE 14, 2022

The mission also sets forward a target of 50% of high-priority data quality issues to be resolved within a period defined by a cross-government framework. These systems will also be hosted – or are planned to be hosted – in appropriate environments aligned to the cross-government cloud and technology infrastructure strategy.

Strategy 105

Strategy IT Digital Transformation Data Processing 105

datapine

MAY 31, 2022

Instead of installing software on your own servers, SaaS companies enable you to rent software that’s hosted, this is typically the case for a monthly or yearly subscription fee. More and more CRM, marketing, and finance-related tools use SaaS business intelligence and technology, and even Adobe’s Creative Suite has adopted the model.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

DataRobot Blog

FEBRUARY 11, 2022

DataRobot’s MLOps product offers a host of features designed to transform organizations’ user experience, firstly, through its model-monitoring agents. These agents apply the concept familiar in the DevOps world—to run models in their preferred environments while monitoring all models centrally. Governance and Trust.

Machine Learning 52

Machine Learning Cost-Benefit ROI Data Processing 52

datapine

APRIL 15, 2020

Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. In the traditional model communication between developers and business users is not a priority. You need to determine if you are going with an on-premise or cloud-hosted strategy.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Alation

OCTOBER 28, 2021

Healthcare is changing, and it all comes down to data. Leaders in healthcare seek to improve patient outcomes, meet changing business models (including value-based care ), and ensure compliance while creating better experiences. Data & analytics represents a major opportunity to tackle these challenges.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

Alation

SEPTEMBER 30, 2022

They go on to explain that, at $100M in ARR, these companies have product-market fit, a scalable GTM model, and a growing customer base. As organizations gain confidence in their ability to wield the power of data, use cases, user types, and applications will multiply. However, we can’t do it alone. Visibility is essential.

Measurement 92

Measurement Metrics Data Governance Sales 92

AWS Big Data

JULY 20, 2023

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 90

Data Lake Analytics Snapshot Optimization 90

DataRobot Blog

DECEMBER 20, 2022

Yet, in the digital transformation era, the pricing and assessment of real estate assets is more difficult than described by brokers’ presentations, valuation reports, and traditional analytical approaches like hedonic models. Datarobot enables users to easily combine multiple datasets into a single training dataset for AI modeling.

Management 59

Management Machine Learning Optimization Modeling 59