Ontotext

APRIL 10, 2024

Most do manual reconciliations which result in downstream challenges and reporting errors. Data Lakes, Data Catalogs, and Findability Organizations approach data lakes as cheap storage. It removes friction and mitigates cost as there’s no need to make copies of the data or pay for its storage or movement.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

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. The user can then consume the data through reports, web applications, mobile apps, or a data platform of their choice. Mitigate risks with a seamless cloud migration.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

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. Flat files – Other systems supply data in the form of flat files of different formats.

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

DataKitchen

JANUARY 3, 2022

For example, teams working under the VP/Directors of Data Analytics may be tasked with accessing data, building databases, integrating data, and producing reports. Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 95

Data Warehouse Testing Data Lake Data-driven 95

Jedox

OCTOBER 22, 2020

In working with clients, these are some of the most common “pain points” I routinely address: Difficulty in extracting data out of legacy systems. Limited self-service reporting across the enterprise. Inability to get data quickly. Data accuracy concerns. More time spent accessing data vs. making data-driven decisions.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

AWS Big Data

APRIL 19, 2023

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

CIO Business Intelligence

SEPTEMBER 21, 2023

In a recent report, he estimated that gen AI software revenues will grow from $3.7 He’s currently tracking 262 gen AI vendors, of which 117 specialize in text generation, and plans to produce a new version of the report in the next six months. billion this year to $36 billion by 2028.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

Peter James Thomas

APRIL 3, 2020

A skilled practitioner, hard at work developing elements of a Structured Reporting Framework. © However, I want to focus on a further pillar in the edifice of easily accessible and comprehensible Insight and Information , a Structured Reporting Framework. In my experience, Structured Reporting Frameworks are much misunderstood.

Dashboards 61

Dashboards Reporting Sales Data Lake 61

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 68

Data Lake Testing Snapshot Sales 68

CIO Business Intelligence

APRIL 4, 2023

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 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 97

Data Warehouse Data Lake Analytics Machine Learning 97

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. What role do technology and IT infrastructure play?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 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 118

Data Lake Unstructured Data Data Warehouse Data Quality 118

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 81

Enterprise Data Warehouse Data Lake Optimization 81

Cloudera

JUNE 30, 2022

Over the past decade, Cloudera has enabled multi-function analytics on data lakes through the introduction of the Hive table format and Hive ACID. Companies, on the other hand, have continued to demand highly scalable and flexible analytic engines and services on the data lake, without vendor lock-in.

Data Lake 85

Data Lake Data Architecture Metadata Data Warehouse 85

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. Pillar 3: Analytics The analytics pillar defines capabilities that help you generate insights on top of your customer data. Organizations using C360 achieved 43.9% faster time to market, and 19.1%

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Alation

DECEMBER 14, 2021

How do you provide access and connect the right people to the right data? AWS has created a way to manage policies and access, but this is only for data lake formation. What about other data sources? Redshift , AWS’ data warehouse that powers data exchange, provides 3x performance (3TB, 30 Tb, 100Tb dataset).

Data Lake 52

Data Lake Data Warehouse Machine Learning Cost-Benefit 52

BizAcuity

APRIL 14, 2022

There are a wide range of problems that are presented to organizations when working with big data. Challenges associated with Data Management and Optimizing Big Data. Unscalable data architecture. Scalable data architecture is not restricted to high storage space. Solutions for Big Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Cloudera

NOVEMBER 29, 2021

The Data Impact Awards 2021 aim to recognize and reward the various organizations taking advantage of the latest Big Data services to successfully manage large amounts of data and thus improve their own organizations and the world. . The company needed a modern data architecture to manage the growing traffic effectively. .

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

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

Peter James Thomas

MAY 3, 2019

Collation of Data to provide Information. This area includes what is often described as “traditional” reporting [3] , Dashboards and analysis facilities. Data Architecture / Infrastructure. When I first started focussing on the data arena, Data Warehouses were state of the art.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

BI-Survey

JANUARY 15, 2023

Data architecture is a topic that is as relevant today as ever. It is widely regarded as a matter for data engineers, not business domain experts. Statements from countless interviews with our customers reveal that the data warehouse is seen as a “black box” by many and understood by few business users.

Data Warehouse 52

Data Warehouse IT Data Architecture Measurement 52

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads.

Data Warehouse 95

Data Warehouse Machine Learning Data-driven Data Lake 95

AWS Big Data

NOVEMBER 13, 2023

11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture. 4:30 PM – 5:30 PM (PDT) Wynn ANT207 | Understand your data with business context. 1:00 PM – 2:00 PM (PDT) Venetian ANT201 | Accelerate innovation with real-time data.

Analytics 109

Analytics Data Lake Data Warehouse Data-driven 109

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 65

Data Architecture Data Lake Machine Learning Data Governance 65

Birst BI

OCTOBER 24, 2019

Data-as-a-Service (DaaS) streamlines the chaos of ungoverned data pipelines and reporting silos created by users who are eager to use data, whether they are simple data inquiries from business analysts to more complex data questions from data science teams. How does DaaS fit into this architecture?

Data Warehouse 51

Data Warehouse Recreation/Entertainment Data Lake Data Architecture 51

AWS Big Data

FEBRUARY 27, 2024

Each data producer within the organization has its own data lake in Apache Hudi format, ensuring data sovereignty and autonomy. These datasets are pivotal for reporting and analytics use cases, powered by services like Amazon Redshift and tools like Power BI.

Data-driven 91

Data-driven Data Lake Data Quality Data Governance 91

Alation

FEBRUARY 20, 2020

After a blockbuster premiere at the Strata Data Conference in New York, the tour will take us to six different states and across the pond to London. Data Catalogs Are the New Black. Gartner’s report, Data Catalogs Are the New Black in Data Management and Analytics , inspired our new penchant for the color black.

Machine Learning 52

Machine Learning Metadata Reporting Data-driven 52

AWS Big Data

DECEMBER 21, 2023

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

Data Lake 85

Data Lake Data Warehouse B2B Data-driven 85

CIO Business Intelligence

AUGUST 3, 2023

As well as keeping its current data accurate and accessible, the company wants to leverage decades of historical data to identify potential risks to ship operations and opportunities for improvement. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

BI-Survey

DECEMBER 22, 2020

The goal is to optimize company data in terms of a common vision in a cooperative and iterative way and thus to accelerate the digital transformation on the basis of data. Architecture and technology play an important role in the transition to a data-driven enterprise. Leverage Your Data.

Data-driven 52

Data-driven Data Strategy Strategy Enterprise 52