Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

BI-Survey

JANUARY 15, 2023

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. Therefore, it is not clear why the costly and apparently flexibility-inhibiting data warehouse is needed at all. But is it really?

Data Warehouse 52

Data Warehouse IT Data Architecture Measurement 52

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 80

Data Lake Data Warehouse Data-driven Optimization 80

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 100

Data Warehouse Data Lake Analytics Machine Learning 100

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 102

Data Lake Management Metrics Data Warehouse 102

Jet Global

DECEMBER 3, 2021

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. Discover Meaning Amid All That Data. Why business intelligence ?

Business Intelligence 52

Business Intelligence Sales OLAP Data Warehouse 52

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

MARCH 18, 2024

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.

Data Warehouse 81

Data Warehouse Visualization Snapshot Data-driven 81

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 128

Data Architecture Data Warehouse Statistics Visualization 128

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 74

Metadata Data Lake Data Processing Data-driven 74

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 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

AWS Big Data

JUNE 28, 2023

They can connect to multiple data streams and pull data directly into Amazon Redshift without staging it in Amazon Simple Storage Service (Amazon S3). After running analytics, the insights can be made available broadly across the organization with Amazon QuickSight , a cloud-native, serverless business intelligence service.

Analytics 67

Analytics Data Warehouse Data Lake Data-driven 67

AWS Big Data

JULY 25, 2023

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool.

Metrics 77

Metrics Data Warehouse Dashboards Snapshot 77

AWS Big Data

JULY 28, 2023

Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service delivering the best price-performance. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools.

Data Lake 65

Data Lake Data Governance Data Warehouse Modeling 65

IBM Big Data Hub

OCTOBER 16, 2023

Using AI for certain business tasks or without guardrails in place may also not align with an organization’s core values. AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It can be used with both on-premise and multi-cloud environments.

Risk 78

Risk Modeling Management Metadata 78

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets.

Data Science 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

Peter James Thomas

AUGUST 18, 2018

Convergent Evolution refers to something else. That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. One of the early promises of a Data Lake approach was that – once all relevant data had been ingested – this would be directly leveraged by Data Scientists to derive insight.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

CIO Business Intelligence

APRIL 26, 2022

Backcountry also lacked many core services critical for an online retailer — no CMS, no analytics, no data platform, and no data lake. On top of that, Nallani had to persuade a team of C-suite executives to invest in a three-year roadmap and technology overhaul that changed every aspect of Backcountry’s business.

Data Lake 97

Data Lake Dashboards Recreation/Entertainment Sales 97

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Sisense

APRIL 26, 2020

Companies and businesses focus a lot on data collection in order to make sure they can get valuable insights out of it. Understanding data structure is a key to unlocking its value. A data’s “structure” refers to a particular way of organizing and storing it in a database or warehouse so that it can be accessed and analyzed.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

SEPTEMBER 21, 2023

Satori integrates natively with both Amazon Redshift provisioned clusters and Amazon Redshift Serverless for easy setup of your Amazon Redshift data warehouse in the secure Satori portal. In part 2, we will explore how to set up self-service data access with Satori to data stored in Amazon Redshift.

Data Warehouse 84

Data Warehouse Interactive Data Architecture Data Lake 84

Cloudera

DECEMBER 19, 2018

Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Business intelligence (BI), an umbrella term coined in 1989 by Howard Dresner, Chief Research Officer at Dresner Advisory Services, refers to the ability of end-users to access and analyze enterprise data.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

AWS Big Data

JULY 13, 2023

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. Basic formatting and readability of the data is standardized here.

Optimization 88

Optimization B2B Data Quality Sales 88

AWS Big Data

APRIL 28, 2023

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools.

Interactive 90

Interactive Metadata Data Warehouse Data-driven 90

Jet Global

FEBRUARY 23, 2024

ETL is beneficial for larger data volumes and diverse sources, and may be necessary for data architects, developers, and administrators considering factors like volume, source diversity, accuracy, and efficiency. Data Migration Data migration refers to the process of transferring data from one location or format to another.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 67

Modeling Sales Data Warehouse Snapshot 67

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 74

Data Quality Testing Data Warehouse Unstructured Data 74

BizAcuity

APRIL 14, 2022

The comprehensive system which collectively includes generating data, storing the data, aggregating and analyzing the data, the tools, platforms and other softwares involved is referred to as Big Data Ecosystem. The best way to avoid poor data quality is having a strict data governance system in place.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Alation

JANUARY 26, 2023

Lack of data governance can summon a whole range of problems, including: Lack of consistency For data to be useful, it should be consistent across all areas. A field might not be entered in the same way across different departments, which makes the data difficult to find and affects the accuracy of business intelligence (BI).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

CIO Business Intelligence

JUNE 29, 2022

If you’re used to using SQL Server Analysis Services for business intelligence, Analysis Services offers that enterprise-grade analytics engine as a cloud service that you can also connect to Power BI. Azure Data Factory. Azure Data Lake Analytics. Microsoft. Azure Analysis Services.

Data Lake 112

Data Lake Analytics Data Warehouse Machine Learning 112

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

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Domino Data Lab

APRIL 3, 2019

“Flashpoint” (2018) – GDPR went into effect, plus major data blunders happened seemingly everywhere. Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 99

Analytics Key Performance Indicator Data Warehouse Data-driven 99