IBM Big Data Hub

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

CDW Research Hub

MARCH 22, 2019

The solution helped make sense of an enormous amount of data about such things as member usage statistics, enrollment rates, contract and payment statuses, staffing and operations. empowering franchisees to use data for business decision-making, and. The integration of the Cognos environment with.

Data Warehouse 66

Data Warehouse Prescriptive Analytics Statistics Big Data 66

CDW Research Hub

JULY 22, 2019

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

Data Warehouse 54

Data Warehouse Business Intelligence Structured Data Data Architecture 54

Cloudera

JULY 15, 2019

Educating Data Analysts at Scale. Cloudera is pleased to announce, in partnership with Coursera, the launch of Modern Big Data Analysis with SQL , a three-course specialization now available on the Coursera platform. This sequence of courses teaches the essential skills for working with data of any size using SQL.

Big Data 56

Big Data Deep Learning Data Warehouse Data-driven 56

AWS Big Data

MARCH 21, 2024

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. ETL and ELT pipelines can be expensive to build and complex to manage.

Data Warehouse 83

Data Warehouse Metrics Statistics Optimization 83

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

FineReport

MAY 6, 2020

Menurut saya, data analyst nampaknya cuma menganalisis data bisnis dan saya tidak tahu bagaimana cara meningkatkan skill saya.” Ini karena dia tidak sepenuhnya menggali nilai dari analisis big data. Software Pemvisualisasi Data: excel, python, software profesional lainnya. Data Warehous: SSIS, SSAS.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 98

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 91

Data Lake Data Warehouse Machine Learning Cost-Benefit 91

AWS Big Data

APRIL 4, 2024

Griffin is an open source data quality solution for big data, which supports both batch and streaming mode. In today’s data-driven landscape, where organizations deal with petabytes of data, the need for automated data validation frameworks has become increasingly critical.

Data Quality 60

Data Quality Data Lake Data Warehouse Data-driven 60

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. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 89

Data Lake Data Warehouse Metadata Data Architecture 89

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 99

Data Lake Management Metrics Data Warehouse 99

Sisense

JANUARY 1, 2020

Data and analytics are all about finding patterns, figuring out what’s next, and creating a better world. In Build the Future of Data , we give you insights into the tools and trends that will define the next era of business. Few worlds have a pace of innovation quite like data and analytics. Read about how Sisense BloX 2.0

Analytics 98

Analytics Digital Transformation Data Warehouse Dashboards 98

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 93

Data Lake Data Warehouse Testing Business Objectives 93

AWS Big Data

DECEMBER 12, 2023

Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries. You can use your preferred SQL clients to analyze your data in an Amazon Redshift data warehouse. He is passionate about automating and solving customer problems with cloud solutions.

Data Warehouse 92

Data Warehouse Management Finance Analytics 92

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation. S3 data lake – Contains the web activity and leads datasets.

Data Lake 82

Data Lake Data Warehouse Marketing Management 82

Cloudera

FEBRUARY 7, 2019

This has become a core component of the fraud management framework for the business, and has helped solidify its role as the trusted keeper of sensitive data. This has increased operational efficiencies significantly because now teams are able to leverage data much more quickly than before. Check out our customer stories.

Big Data 64

Big Data Data Analytics Analytics Data Architecture 64

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Digital Transformation 106

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 106

AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. For more information, see ElectricityLoadDiagrams20112014 Data Set (Dua, D. and Karra Taniskidou, E.

Forecasting 80

Forecasting Data Warehouse Machine Learning Modeling 80

Jen Stirrup

MAY 3, 2020

Azure Synapse is an Azure-based cloud analytics service that provides insights on all data across data warehouses and big data analytics systems. It combines familiar SQL technologies such as data warehousing with Spark technologies used in big data analytics. Azure Synapse docs on GitHub.

Big Data 56

Big Data Data Warehouse Machine Learning Business Intelligence 56

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 89

Data Warehouse Data-driven Machine Learning B2B 89

AWS Big Data

SEPTEMBER 19, 2023

However, our legacy data warehouse-based solution was not equipped for this challenge. However, with a minimum data freshness of 10 minutes, this architecture inherently didn’t align with the near real-time fraud detection use case. He enjoys being at the intersection of big data and programming language theory.

Analytics 75

Analytics Risk Big Data Machine Learning 75

Cloudera

DECEMBER 19, 2018

Natural language analytics and streaming data analytics are emerging technologies that will impact the market. Cloud computing has passed the tipping point, with most organizations comfortable moving critical data and applications to the public cloud. Big Data Technologies and Architectures.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

AWS Big Data

OCTOBER 5, 2023

Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery. Architecture Let’s review the architecture to transfer data from Google BigQuery to Amazon S3 using Amazon AppFlow.

Data Warehouse 82

Data Warehouse Machine Learning Data Integration Data-driven 82

AWS Big Data

OCTOBER 20, 2023

Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He is passionate about architecting fast-growing data environments, diving deep into distributed big data software like Apache Spark, building reusable software artifacts for data lakes, and sharing knowledge in AWS Big Data blog posts.

Data Lake 80

Data Lake Big Data Consulting Data Warehouse 80

Howard Dresner

JANUARY 8, 2013

Dear Friends, Since last year I began supporting a new Business Intelligence blog on the Sandhill.com website , called "Dresner's Point". BIWisdom tweetchat tribe members were facing off in response to the question of whether the EDW (electronic data warehouse) is dead.

Business Intelligence 45

Business Intelligence Data Warehouse Data Processing Big Data 45

Paul Blogs on BI

NOVEMBER 13, 2023

If the data is not correct then its garbage in and garbage out, or as I have always said : BIG DATA + BAD DATA = BIG BAD DATA However, when it comes to a good data strategy, it’s not just about the quality of the data, it’s also about the design and functionality of the structure where it is housed.

Data Strategy 52

Data Strategy Strategy Gap analysis Data Warehouse 52

Data Virtualization

OCTOBER 22, 2021

Since its first incarnation almost 35 years ago in my IBM Systems Journal article, the data warehouse (DW) has remained a key architectural pattern for decision-making support. The post Weaving Architectural Patterns: I – Data Fabric appeared first on Data Virtualization blog.

Data Warehouse 52

Data Warehouse Reporting IT Metadata 52

Data Virtualization

OCTOBER 21, 2021

Since its first incarnation almost 35 years ago in my IBM Systems Journal article, the data warehouse (DW) has remained a key architectural pattern for decision-making support. The post Weaving Architectural Patterns: I – Data Fabric appeared first on Data Virtualization blog.

Data Warehouse 52

Data Warehouse Reporting IT Metadata 52

erwin

AUGUST 15, 2022

This blog is based upon a recent webcast that can be viewed here. For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. Moreover, this blog will provide readers with a firm foundation for NoSQL and data lakes as they move to the cloud.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

AWS Big Data

JUNE 2, 2023

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytic workloads. He has worked with building data warehouses and big data solutions for over 13 years.

Metadata 106

Metadata Data Warehouse Big Data Testing 106

CDW Research Hub

OCTOBER 12, 2021

One of the biggest obstacles to this needed agility is poorly integrated data, which results in five key challenges: The inability to support a logical data warehouse architecture to enable advanced analytics. Unreliable Data as a Service (DaaS) implementations. Silos within big data implementations.

Data Warehouse 52

Data Warehouse Big Data Data Architecture Cost-Benefit 52

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. One of the most common use cases for data preparation on Amazon Redshift is to ingest and transform data from different data stores into an Amazon Redshift data warehouse.

Visualization 74

Visualization Data Warehouse Big Data Data Lake 74

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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. Overall data architecture and strategy. Use case priority and workload identifications.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

Sisense

APRIL 17, 2020

Money never sleeps and neither does your data. In Monetizing Your Data , we look at digital transformation: the ways of turning data into new revenue streams and apps that boost income, increase stickiness, and help your company thrive in the world of Big Data.

Data Strategy 81

Data Strategy Strategy Digital Transformation Data Warehouse 81