CIO Business Intelligence

JUNE 24, 2022

Approximately 61% of APAC organizations have failed to build robust and successful digital business business models, primarily due to unsound practices of enterprise architecture (EA) teams, according to a report from Forrester. Digital Transformation

Modeling 96

Modeling Digital Transformation Data Architecture Data-driven 96

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. The past decades of enterprise data platform architectures can be summarized in 69 words. DDD divides a system or model into smaller subsystems called domains.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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 88

Enterprise Data Warehouse Data Lake Optimization 88

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 88

Data Warehouse Visualization Data-driven Data Architecture 88

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 104

Data Warehouse Data Lake Analytics Machine Learning 104

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 115

Data Warehouse Cost-Benefit Sales Data-driven 115

AWS Big Data

NOVEMBER 14, 2023

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze all your data at petabyte scale, using standard SQL and your existing business intelligence (BI) tools. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift.

Data Warehouse 60

Data Warehouse Analytics Testing Cost-Benefit 60

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 93

Data Lake Data Warehouse Data-driven B2B 93

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

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 98

Data-driven Data Lake Data Quality Data Governance 98

Smarten

JUNE 1, 2022

An integrated solution provides single sign-on access to data sources and data warehouses.’. The integrated augmented analytics approach includes simple tenant management to deploy with a shared data model for single-tenant mode or an isolated data model for multi-tenant mode and software as a service (SaaS) applications.

Data Warehouse 76

Data Warehouse Software Data Architecture Consulting 76

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).

Data Lake 101

Data Lake Data Warehouse Testing Business Objectives 101

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. How is data, process, and model drift managed for reliability?

Machine Learning 132

Machine Learning Cost-Benefit Data-driven Strategy 132

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 96

Data Warehouse Data-driven Machine Learning B2B 96

CIO Business Intelligence

APRIL 25, 2022

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. They require specific data inputs, models, algorithms and they deliver very specific recommendations.

Recreation/Entertainment 111

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 111

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

CIO Business Intelligence

MARCH 26, 2024

Mr. Cao elaborated that it taps into large artificial intelligence (AI) models to visualise correlations as well as changes to networks, traffic and applications in real time. Meanwhile, under the third prong of zero trust, Huawei stated the need to build “multi-layer in-depth defense” to ensure service and data security.

Strategy 59

Strategy Uncertainty Finance Digital Transformation 59

Cloudera

NOVEMBER 1, 2022

Through modern data architectures powered by CDP, including Cloudera-enabled data fabric, data lakehouse, and data mesh , DoD agencies can rapidly provision and manage innovative data engineering, data warehouse, and machine learning environments, with access to secured supply chain data stored in CDP Private Cloud.

Cost-Benefit 84

Cost-Benefit Data Architecture Risk IoT 84

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Data can be organized into three different zones, as shown in the following figure.

Data Lake 107

Data Lake Sales Data Warehouse Snapshot 107

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 84

Data Lake Data Architecture Metadata Data Warehouse 84

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads.

Analytics 99

Analytics Data Warehouse Testing Dashboards 99

AWS Big Data

JANUARY 31, 2023

In this post, we are excited to summarize the features that the AWS Glue Data Catalog, AWS Glue crawler, and Lake Formation teams delivered in 2022. Whether you are a data platform builder, data engineer, data scientist, or any technology leader interested in data lake solutions, this post is for you.

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. Reduce the total cost of ownership of the data infrastructure.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

CIO Business Intelligence

APRIL 25, 2022

Similarly, many organizations have built data architectures to remain competitive, but have instead ended up with a complex web of disparate systems which may be slowing them down. Aligning data. A real-time data architecture should be designed with a set of aligned data streams that flow easily throughout the data ecosystem.

Data Architecture 95

Data Architecture Digital Transformation Data-driven Strategy 95

AWS Big Data

MARCH 26, 2024

Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 71

Data Strategy Strategy Data Warehouse Prescriptive Analytics 71

CIO Business Intelligence

JUNE 23, 2023

There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value. Even physical assets can be monetized this way.

Data Strategy 105

Data Strategy Strategy Visualization Consulting 105

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. It’s raw, unprocessed data straight from the source.

Data Warehouse 109

Data Warehouse Testing Data Quality Reporting 109

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Unstructured Data 61

Unstructured Data Data Lake Data Warehouse Machine Learning 61

CDW Research Hub

OCTOBER 12, 2021

As organizations grow and evolve, many find a need for more sophisticated analytics across an ever-increasing amount of digital and consumer data. But most legacy data architectures do not have a unified data model, and they are hard-wired toward specific BI tools that do not support self-service analytics.

Data Warehouse 52

Data Warehouse Big Data Data Architecture Cost-Benefit 52

Cloudera

OCTOBER 11, 2022

Because that is how models learn. You also need to continually feed models new data to keep them up to date. Most AI apps and ML models need different types of data – real-time data from devices, equipment, and assets and traditional enterprise data – operational, customer, service records. .

Snapshot 90

Snapshot Data Science Digital Transformation Metadata 90

Cloudera

APRIL 13, 2021

But while the company is united by purpose, there was a time when its teams were kept apart by a data platform that lacked the scalability and flexibility needed for collaboration and efficiency. Disparate data silos made real-time streaming analytics, data science, and predictive modeling nearly impossible.

Enterprise 74

Enterprise Cost-Benefit Data Warehouse Data Architecture 74

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 98

Dashboards Analytics Metadata Data Warehouse 98

Ontotext

APRIL 10, 2024

Knowledge graphs and semantic metadata Knowledge graphs (KGs) are the key to: Advanced Data Architecture & Models like Data Fabric, Data Mesh Unified Data Access Semantic Data Integration These fundamental capabilities of KGs enable them to bridge the chasm between information and knowledge in the DIKW pyramid.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Smarten

MAY 30, 2023

Integrate objects (Dashboards, Crosstab, Tabular, KPIs, Graphs, Reports, models, Clickless Analytics and more).’ It is also supported by advanced analytics components including natural language processing (NLP) search analytics, and assisted predictive modeling to enable the Citizen Data Scientist culture. Deploy anywhere!

Slice and Dice 52

Slice and Dice Business Intelligence Cost-Benefit Dashboards 52

CIO Business Intelligence

SEPTEMBER 14, 2023

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas.

Analytics 132

Analytics Data Science Unstructured Data Data mining 132

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. Data fabric does not replace data warehouses, data lakes, or data lakehouses.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52