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. Security Data Lake. Learn more about our Security Data Lake Solution.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

TDAN

JUNE 16, 2020

When companies embark on a journey of becoming data-driven, usually, this goes hand in and with using new technologies and concepts such as AI and data lakes or Hadoop and IoT. Suddenly, the data warehouse team and their software are not the only ones anymore that turn data […].

Data Warehouse 52

Data Warehouse Data-driven Data Lake IoT 52

CIO Business Intelligence

NOVEMBER 28, 2023

But at the other end of the attention spectrum is data management, which all too frequently is perceived as being boring, tedious, the work of clerks and admins, and ridiculously expensive. Still, to truly create lasting value with data, organizations must develop data management mastery.

Management 131

Management Data Architecture Data Lake Data Strategy 131

Data Virtualization

JANUARY 19, 2023

Reading Time: 2 minutes Today, many businesses are modernizing their on-premises data warehouses or cloud-based data lakes using Microsoft Azure Synapse Analytics. Unfortunately, with data spread.

Data Analytics 52

Data Analytics Data Lake Data Warehouse Analytics 52

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. Partner solutions to boost functionality, adoption.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

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. Companies feel locked into these systems as they are often tied to business-critical operations. Reduce the total cost of ownership of the data infrastructure.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

TDAN

MAY 31, 2022

As we enter a new cloud-first era, advancements in technology have helped companies capture and capitalize on data as much as possible. Deciding between which cloud architecture to use has always been a debate between two options: data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Technology Data Architecture 52

IBM Big Data Hub

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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. This process has been scheduled to run daily, ensuring a consistent batch of fresh data for analysis.

Data Warehouse 102

Data Warehouse Testing Data Quality Reporting 102

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 145

Machine Learning Cost-Benefit Data-driven Strategy 145

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

Cloudera

DECEMBER 19, 2018

Growth factors and business priority are ever changing. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. This enables you to easily manage and maintain your tables on transactional data lakes.

Data Lake 91

Data Lake Data Warehouse Metadata Data Architecture 91

Jedox

OCTOBER 22, 2020

Too often, Finance & FP&A has been constrained by the data architecture our organizations have built (or maybe not built) over the past twenty or so years. Typically, we take our multiple data sources and perform some level of ETL on the data.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Towards Data Science ). Deploying modern data architectures. Forrester ).

Data Architecture 75

Data Architecture Data Lake Metadata Data Warehouse 75

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

CIO Business Intelligence

SEPTEMBER 21, 2023

To make all this possible, the data had to be collected, processed, and fed into the systems that needed it in a reliable, efficient, scalable, and secure way. Data warehouses then evolved into data lakes, and then data fabrics and other enterprise-wide data architectures.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

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 111

Data Lake Metadata Optimization Statistics 111

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

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 90

Data Warehouse Data Lake Analytics Data Science 90

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 99

Data Warehouse Data Lake Analytics Machine Learning 99

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. It required a different data platform solution. It was Datawarehouse.

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 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

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

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 83

Data Lake Data Architecture Metadata Data Warehouse 83

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Enterprise 75

Enterprise Management Strategy Data Lake 75

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

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 59

Management Enterprise Strategy IT 59

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 52

Management Enterprise Strategy IT 52

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

Peter James Thomas

MAY 3, 2019

The flip side is that making the necessary investments to provide even basic information has been at the heart of the successful business turnarounds that I have been involved in. The bulk of Business Intelligence efforts would also fall into this area, but there is some overlap with the area I next describe as well.

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

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 110

Analytics Data Lake Data Warehouse Data-driven 110

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 64

Data Architecture Data Lake Machine Learning Data Governance 64