IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 78

Risk Modeling Management Metadata 78

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 92

Data Governance Unstructured Data Metadata Data Lake 92

BizAcuity

NOVEMBER 22, 2022

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

AWS Big Data

JANUARY 31, 2023

In addition, data governance is required to comply with an increasingly complex regulatory environment with data privacy (such as GDPR and CCPA) and data residency regulations (such as in the EU, Russia, and China). Sharing data using LF-tags helps scale permissions and reduces the admin work for data lake builders.

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. In this way, the Cloud Data Warehouse Accelerator enables a seamless transition to Snowflake. Mitigate risks with a seamless cloud migration.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

AWS Big Data

JUNE 28, 2023

Furthermore, the time required to build or change pipelines makes the data unfit for near-real-time use cases such as detecting fraudulent transactions, placing online ads, and tracking passenger train schedules. Improving the zero-ETL performance is a continuous goal for AWS.

Analytics 66

Analytics Data Warehouse Data Lake Data-driven 66

BizAcuity

APRIL 1, 2023

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

Timo Elliott

MAY 27, 2022

I was at the Gartner Data & Analytics conference in London a couple of weeks ago and I’d like to share some thoughts on what I think was interesting, and what I think I learned…. First, data is by default, and by definition, a liability , because it costs money and has risks associated with it.

Data Analytics 123

Data Analytics Analytics Recreation/Entertainment Data Lake 123

erwin

OCTOBER 31, 2019

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed. So being prepared means you can minimize your risk exposure and the damage to your reputation.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

erwin

SEPTEMBER 3, 2020

You can collect complete application ecosystem information; objectively identify connections/interfaces between applications, using data; provide accurate compliance assessments; and quickly identify security risks and other issues. You can better manage risk because of real-time data coming into the EA space.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

Cloudera

FEBRUARY 12, 2024

Most cloud users do not like opening firewall rules because that will introduce the risk of exposing private data on the internet. For data warehouse: create data warehouses through the Cloudera command line interface with the parameter “privateDNSZoneAKS”: set to”None.”

Data Warehouse 52

Data Warehouse Machine Learning Data Lake Management 52

Cloudera

NOVEMBER 12, 2020

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. Key areas of concern are: .

Data Warehouse 103

Data Warehouse Reporting Risk Cost-Benefit 103

Jet Global

JANUARY 15, 2021

You might measure those costs in different ways, including actual dollars and cents, staff time, added complexity, and risk. There are numerous soft costs involving risk and potential business disruption. A non-developer can build a custom data warehouse with Jet Analytics in as little as 30 minutes.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. What is a data fabric?

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

Alation

FEBRUARY 13, 2020

We also have some primary insurance entities in the group, but the main thing about reinsurance is that we’re taking care of the big and complex risks in the world. A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives.

Data-driven 52

Data-driven Data Lake Enterprise Analytics 52

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Lack of a solid data governance foundation increases the risk of data-security incidents.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

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.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

OCTOBER 6, 2022

Certain technologies require skills to maintain them that are harder to find, which is a further risk as those resources move towards retirement age. For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases. Strategies to maximize impact.

Digital Transformation 89

Digital Transformation Cost-Benefit Data Lake Machine Learning 89

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. Given the risks of staying intact to primitive practices is scary in itself.

Management 66

Management Data Lake Uncertainty Data Warehouse 66

erwin

JANUARY 11, 2019

Consider the problematic issue of manually mapping source system fields (typically source files or database tables) to target system fields (such as different tables in target data warehouses or data marts). And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. Improving the supply chain and mitigating its risk.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

CIO Business Intelligence

APRIL 6, 2022

Large enterprises that have traditionally been risk-averse are now adopting new approaches such as investing in design and innovation studios, partnering with startups for niche capabilities, and gaining early access to technology through strategic partnerships with hyper-scalers.

Experimentation 103

Experimentation Data Lake Uncertainty Enterprise 103

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 59

Data-driven Enterprise Data Governance Data Lake 59

Cloudera

SEPTEMBER 2, 2020

Additionally, lines of business (LOBs) are able to gain access to a shared data lake that is secured and governed by the use of Cloudera Shared Data Experience (SDX). Build use case-driven data applications with easy-to-use, self-serve experiences, such as Data Warehouse and Machine Learning, on CDP Private Cloud.

Cost-Benefit 67

Cost-Benefit Data Warehouse Data Lake Machine Learning 67

CIO Business Intelligence

APRIL 12, 2023

Most current data architectures were designed for batch processing with analytics and machine learning models running on data warehouses and data lakes. All of this needs to work cohesively in a real-time ecosystem and support the speed and scale necessary to realize the business benefits of real-time AI.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

CIO Business Intelligence

SEPTEMBER 6, 2022

As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence. Establishing a clear and unified approach to data. Very has come full circle as a business built on catalog data, but it took some introspection in order to figure out the best way to get there.

IT 98

IT Forecasting Data Lake Enterprise 98

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

JANUARY 18, 2021

Perhaps more importantly, it provides an opportunity for the organization to implement measures in advance that can reduce risk, lower costs, and improve the end result. Because they are separate from the core ERP application, there is no risk that they will corrupt that core functionality. Start with a Functional Review.

Data Lake 98

Data Lake Reporting Cost-Benefit Finance 98

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

Cloudera

MAY 12, 2021

We welcome organizations that have built and deployed use cases for enterprise-scale machine learning and have industrialized AI to automate, secure, and optimize data-driven decision-making and/or applications to enter this category. Read more about last years Data Impact Award winners. HYBRID & MULTI-CLOUD INNOVATION.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

CIO Business Intelligence

SEPTEMBER 8, 2022

“The enormous potential of real-time data not only gives businesses agility, increased productivity, optimized decision-making, and valuable insights, but also provides beneficial forecasts, customer insights, potential risks, and opportunities,” said Krumova.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

Jet Global

JANUARY 6, 2021

Getting to the cloud, though, will require one more big project, with all of the cost, complexity, and risk that go along with such endeavors. How can businesses manage the process to achieve positive results while maintaining budget and risks within acceptable parameters? Here are some best practices: Start the Process Early.

Cost-Benefit 98

Cost-Benefit Testing Finance Reporting 98

CIO Business Intelligence

APRIL 22, 2024

Questi requisiti sono suddivisi in tre macroaree: governance, risk management e controllo della catena di fornitura. Per esempio, “i PoC aiutano a definire i parametri in base ai quali organizzare i data lake o i criteri per la digitalizzazione dei workflow.

Data Lake 105

Data Lake Testing Management IoT 105

CIO Business Intelligence

SEPTEMBER 21, 2023

The phrase “existential risk” is now everywhere—not in the sense the AI would destroy humanity, but that it would make business functions, or even entire companies, obsolete. If you take something slightly risky and make it a thousand times bigger, the risks are amplified,” he says. But it’s a sign of what’s to come. “If

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. Instead, we can use automation to speed up the process of migration and reduce heavy lifting tasks, costs, and risks. He is passionate about big data and data analytics.

Metadata 76

Metadata Testing Data Lake Consulting 76

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52