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 97

Data-driven Data Lake Data Quality Data Governance 97

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

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

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 95

Analytics Data Lake Metadata Cost-Benefit 95

BizAcuity

NOVEMBER 22, 2022

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

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

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 81

Data Lake Data Architecture Data-driven Data Warehouse 81

BI-Survey

NOVEMBER 23, 2021

However, the operational data stored in data silos was not suitable for this task. Many companies therefore built a data warehouse to consolidate their operational data silos. Data-based insights are being used to automate decisions. Data black holes: the high cost of supposed flexibility.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

BizAcuity

APRIL 1, 2023

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. For this reason, Snowflake is often the cloud-native data warehouse of choice.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

Cloudera

SEPTEMBER 12, 2022

Combining and analyzing both structured and unstructured data is a whole new challenge to come to grips with, let alone doing so across different infrastructures. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse. Unified data fabric. Better together.

Unstructured Data 74

Unstructured Data Data Architecture Data Lake Snapshot 74

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

CIO Business Intelligence

APRIL 12, 2023

After walking his executive team through the data hops, flows, integrations, and processing across different ingestion software, databases, and analytical platforms, they were shocked by the complexity of their current data architecture and technology stack. It isn’t easy.

Machine Learning 138

Machine Learning Cost-Benefit Data-driven Strategy 138

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 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

BizAcuity

APRIL 14, 2022

Be it supply chain resilience, staff management, trend identification, budget planning, risk and fraud management, big data increases efficiency by making data-driven predictions and forecasts. With adequate market intelligence, big data analytics can be used for unearthing scope for product improvement or innovation.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Cloudera

NOVEMBER 27, 2023

Cloudera Perspective: Deployment architecture matters. Cloud-only solutions will not meet the needs for many use cases and run the risk of creating additional barriers for organizations. For now, Flink plus Iceberg is the compute plus storage solution for streaming data. Hybrid matters!

Data Lake 82

Data Lake Advertising ROI Data Warehouse 82

Alation

APRIL 19, 2022

Further, data modernization reduces data security and privacy compliance risks. Its process includes identifying sensitive information so you can limit users’ access to data precisely and efficiently. In that sense, data modernization is synonymous with cloud migration.

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

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 129

Enterprise Consulting Modeling Cost-Benefit 129

Alation

APRIL 14, 2022

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged. Scheduling. Target Matching.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52