IBM Big Data Hub

MAY 9, 2023

We can use foundation models to quickly perform tasks with limited annotated data and minimal effort; in some cases, we need only to describe the task at hand to coax the model into solving it. But these powerful technologies also introduce new risks and challenges for enterprises.

Enterprise 134

Enterprise Technology Modeling Cost-Benefit 134

CIO Business Intelligence

OCTOBER 25, 2023

From IT, to finance, marketing, engineering, and more, AI advances are causing enterprises to re-evaluate their traditional approaches to unlock the transformative potential of AI. What can enterprises learn from these trends, and what future enterprise developments can we expect around generative AI?

Enterprise 133

Enterprise Risk Manufacturing Finance 133

erwin

SEPTEMBER 3, 2020

Why should you integrate data governance (DG) and enterprise architecture (EA)? Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

CIO Business Intelligence

APRIL 25, 2024

With questions around ROI, increasing outlay, and corporate scrutiny on IT cost savings on the rise, CIOs must know not only what contributes to their organization’s overall cloud spend but also how to optimize it. Evolving enterprise needs often outpace the product roadmaps of SaaS cost optimization solutions providers.

Management 115

Management Optimization Strategy Enterprise 115

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 98

Enterprise Data Lake Data Collection Data-driven 98

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 78

Data Lake Data Governance Cost-Benefit Machine Learning 78

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 82

Enterprise Data Lake Data Collection Data-driven 82

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

CIO Business Intelligence

SEPTEMBER 20, 2023

The data can also help us enrich our commodity products. How are you populating your data lake? We’ve decided to take a practical approach, led by Kyle Benning, who runs our data function. Then our analytics team, an IT group, makes sure we build the data lake in the right sequence.

Data Lake 134

Data Lake Data-driven Dashboards Risk 134

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 111

Data Lake Analytics Dashboards Metrics 111

AWS Big Data

NOVEMBER 10, 2023

Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency. Additionally, you’ll benefit from performance improvements through pushdown optimizations, further enhancing the efficiency of your operations. options(**read_config).option("query",

Data Processing 91

Data Processing Data Lake Data Warehouse Optimization 91

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 91

Data Lake Snapshot Big Data Data-driven 91

DataKitchen

NOVEMBER 4, 2021

It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows. The DataKitchen Platform is a “ process hub” that masters and optimizes those processes. Cloud computing has made it much easier to integrate data sets, but that’s only the beginning.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

AWS Big Data

JANUARY 12, 2024

Leadership and development teams can spend more time optimizing current solutions and even experimenting with new use cases, rather than maintaining the current infrastructure. With the ability to move fast on AWS, you also need to be responsible with the data you’re receiving and processing as you continue to scale.

Data Lake 92

Data Lake Cost-Benefit Visualization Structured Data 92

DataKitchen

AUGUST 19, 2021

Data mesh and DataOps provide the organization, enterprise architecture, and workflow automation that together enable a relatively small data team to address the analytics needs of hundreds of active business users. Figure 1: Data requirements for phases of the drug product lifecycle. The new Recipes run, and BOOM!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 82

Data Lake Big Data Consulting Data Warehouse 82

CIO Business Intelligence

APRIL 11, 2022

Although centralized data models and architectures, including data lakes and data-center-based warehouses and repositories, may no longer be the leading data strategy, elements of a centralized approach remain a critical part of the mix. over last year. In many cases, this created a mostly unusable swamp.

Optimization 52

Optimization Data Lake Data Strategy Internet of Things 52

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

CIO Business Intelligence

APRIL 1, 2024

Cleanse your data. GenAI requires high-quality data. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. Learn more about how Dell Generative AI Solutions.

Data Lake 142

Data Lake Consulting Uncertainty Risk 142

IBM Big Data Hub

APRIL 15, 2024

The industry must continually optimize process, improve efficiency, and improve overall equipment effectiveness. Or we create a data lake, which quickly degenerates to a data swamp. Generative AI empowers enterprises at the strategic core of their business. The manufacturing industry is in an unenviable position.

Manufacturing 104

Manufacturing Contextual Data Knowledge Discovery Modeling 104

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3). Choose Create endpoint.

Data Lake 95

Data Lake Data Warehouse Testing Business Objectives 95

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

Cloudera

MARCH 5, 2024

But even with its rise, AI is still a struggle for some enterprises. AI, and any analytics for that matter, are only as good as the data upon which they are based. Cloudera is now the only provider to offer an open data lakehouse with Apache Iceberg for cloud and on-premises. And that’s where the rub is.

Snapshot 86

Snapshot Data Lake Enterprise Data Governance 86

Smart Data Collective

FEBRUARY 23, 2022

There are a lot of benefits of data scalability. The size and the variety of data that enterprises have to deal with have become more complex and larger. Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. How to improve indexing.

Data Lake 98

Data Lake Cost-Benefit Optimization Big Data 98

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

CIO Business Intelligence

MAY 23, 2022

Enterprises moving their artificial intelligence projects into full scale development are discovering escalating costs based on initial infrastructure choices. Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex.

Experimentation 137

Experimentation Cost-Benefit Data Lake Data Science 137

CIO Business Intelligence

JANUARY 10, 2024

Optimizing cloud investments requires close collaboration with the rest of the business to understand current and future needs, building effective FinOps teams, partnering with providers, and ongoing monitoring of key performance metrics. You worry you don’t have enough capacity, so you overprovision,” he says.

Cost-Benefit 124

Cost-Benefit Measurement Optimization Metrics 124

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. A risk issue in one financial institution could result in a domino effect for many.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

Cloudera

JUNE 7, 2023

The revised ZTMM is organized by five categories or pillars: identity, devices, networks, applications and workloads, and data, and four levels of maturity: traditional, initial, advanced, and optimal. Moving to the “optimal” stage of maturity is critical to eliminating unauthorized access by bad actors, both foreign and domestic.

Metadata 78

Metadata Data Lake Optimization Modeling 78

CIO Business Intelligence

OCTOBER 25, 2022

Finally, the problem was shared by the enterprise at large. And they needed a place to store that data—they lacked infrastructure that could manage both the terabytes pouring off the sensors and the coupling customer data (which resided within enterprise platforms such as ERP, transportation, and supply & demand planning).

Data Strategy 145

Data Strategy Strategy Data Lake Data-driven 145

Timo Elliott

DECEMBER 14, 2022

The future is enabled by technology, but it’s not about the technical infrastructures: it’s about optimizing end-to-end processes, business capabilities, and business ecosystems. You lose the roots: the metadata, the hierarchies, the security, the business context of the data. So how do organizations do that? Business Process.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

Cloudera

OCTOBER 6, 2022

Gartner : “Digital transformation can refer to anything from IT modernization (for example, cloud computing), to digital optimization, to the invention of new digital business models.”. For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases.

Digital Transformation 84

Digital Transformation Cost-Benefit Data Lake Machine Learning 84

CIO Business Intelligence

JULY 26, 2023

We’ve been on a journey for the last six years or so to build out our platforms,” says Cox, noting that Keller Williams uses MLS, demographic, product, insurance, and geospatial data globally to fill its data lake. “We

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

AWS Big Data

APRIL 11, 2023

Accurately predicting demand for products allows businesses to optimize inventory levels, minimize stockouts, and reduce holding costs. Solution overview In today’s highly competitive business landscape, it’s essential for retailers to optimize their inventory management processes to maximize profitability and improve customer satisfaction.

Forecasting 74

Forecasting Management IoT Data-driven 74