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

AWS Big Data

OCTOBER 17, 2023

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

Data Warehouse 87

Data Warehouse Data Processing Data Lake Management 87

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Cloudera

JANUARY 11, 2021

At the same time, Central IT must juggle cost and risk. In data-driven organizations, to fulfill its charter to democratize data and provide on-demand, quality computing services in a secure, compliant environment, IT must replace legacy approaches and update technologies. How self-service data warehousing frees IT resources.

Data Warehouse 62

Data Warehouse Data Lake Cost-Benefit Machine Learning 62

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data modeling basics.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 102

Data Warehouse Data Lake Analytics Machine Learning 102

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 72

Risk Modeling Management Metadata 72

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

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 101

Data Lake Data Warehouse Management Risk 101

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

Data Lake 94

Data Lake Unstructured Data Data Warehouse Data Quality 94

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

AWS Big Data

FEBRUARY 27, 2024

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.

Data-driven 96

Data-driven Data Lake Data Quality Data Governance 96

AWS Big Data

MAY 16, 2024

As an AWS Partner, CARTO offers a software solution on the curated digital catalog AWS Marketplace that seamlessly integrates distinctive capabilities for spatial visualization, analysis, and app development directly within the AWS data warehouse environment. To learn more, visit CARTO.

Data Warehouse 109

Data Warehouse Visualization Cost-Benefit Optimization 109

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. And you also already know siloed data is costly, as that means it will be much tougher to derive novel insights from all of your data by joining data sets.

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

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 97

Data Governance Unstructured Data Metadata Data Lake 97

Cloudera

NOVEMBER 5, 2020

Many organizations struggle to meet growing and variable data warehouse demands. This is exactly what Cloudera Data Platform (CDP) provides to the Cloudera Data Warehouse. CDP is a data platform that is optimized for both business units and central IT. .

Data Lake 72

Data Lake Data Warehouse Metadata Optimization 72

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

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 93

Data Analytics Analytics Data Warehouse Data Lake 93

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 84

Data Lake Data Governance Data Architecture Machine Learning 84

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

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model?

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Modeling 66

IBM Big Data Hub

MAY 9, 2023

With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments. Savings may vary depending on configurations, workloads and vendors.

Data Warehouse 107

Data Warehouse Machine Learning Cost-Benefit Metadata 107

CIO Business Intelligence

AUGUST 3, 2023

But reaching all these goals, as well as using enterprise data for generative AI to streamline the business and develop new services, requires a proper foundation. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 84

Analytics Data Lake Metadata Cost-Benefit 84

CIO Business Intelligence

OCTOBER 19, 2022

“So, at Zebra, we created a hub-and-spoke model, where the hub is data engineering and the spokes are machine learning experts embedded in the business functions. We kept the data warehouse but augmented it with a cloud-based enterprise data lake and ML platform. What about risk? What about security?

IT 108

IT Digital Transformation Data Warehouse Risk 108

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 71

Analytics Data Warehouse Data Lake Data-driven 71

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

DataKitchen

JULY 27, 2023

Azure Synapse Analytics Pipelines: Azure Synapse Analytics (formerly SQL Data Warehouse) provides data exploration, data preparation, data management, and data warehousing capabilities. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

MARCH 26, 2024

Enrichment typically involves adding demographic, behavioral, and geolocation data. You can use third-party data products from AWS Marketplace delivered through AWS Data Exchange to gain insights on income, consumption patterns, credit risk scores, and many more dimensions to further refine the customer experience.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

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

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 60

Data Architecture Data Lake Machine Learning Data Governance 60

Cloudera

AUGUST 9, 2022

Data platforms are no longer skunkworks projects or science experiments. As customers import their mainframe and legacy data warehouse workloads, there is an expectation on the platform that it can meet, if not exceed, the resilience of the prior system and its associated dependencies. Why disaster recovery? Conclusion.

Data Lake 77

Data Lake Data Warehouse Data-driven IoT 77

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