DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

Cloudera

JANUARY 19, 2022

Gartner® recognized Cloudera in three recent reports – Magic Quadrant for Cloud Database Management Systems (DBMS), Critical Capabilities for Cloud Database Management Systems for Analytical Use Cases and Critical Capabilities for Cloud Database Management Systems for Operational Use Cases. Download the reports to see the detailed scores .

Reporting 87

Reporting Data Warehouse Data Lake Machine Learning 87

CIO Business Intelligence

OCTOBER 13, 2023

Data architects are frequently part of a data science team and tasked with leading data system projects. They often report to data infrastructure and data science leads. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

MAY 25, 2023

Many organizations today are using AWS Glue to build ETL pipelines that bring data from disparate sources and store the data in repositories like a data lake, database, or data warehouse for further consumption. The email is formatted via HTML output that provides tables for the aggregated job run data.

Reporting 71

Reporting Metrics Optimization Data Lake 71

Ontotext

APRIL 10, 2024

Drowning in Data, Thirsting for Context We’ve heard the saying, “Data, data everywhere. ” As more data accumulates, context gets diluted and lost. Bad Data Tax One of the reasons for this is what we call “ bad data tax ”. Not a drop of insight.”

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 87

Data Lake Big Data Consulting Data Warehouse 87

CIO Business Intelligence

SEPTEMBER 12, 2022

The chief information and digital officer for the transportation agency moved the stack in his data centers to a best-of-breed multicloud platform approach and has been on a mission to squeeze as much data out of that platform as possible to create the best possible business outcomes. NJ Transit.

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

AWS Big Data

MARCH 7, 2023

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. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

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. The data typically encompasses all transactions and operations that the business engages in.

Data Warehouse 109

Data Warehouse Testing Data Quality Reporting 109

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics. What Are Data Entities?

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

APRIL 4, 2024

Automated data validation frameworks offer a streamlined solution by efficiently comparing large datasets, identifying discrepancies, and ensuring data accuracy at scale. Although this solution is designed to seamlessly interact with both Hive Metastore and the AWS Glue Data Catalog, we use the Data Catalog as our example in this post.

Data Quality 65

Data Quality Data Lake Data Warehouse Data-driven 65

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. When running properly, it provides timely and trustworthy information.

Metrics 99

Metrics Data Lake Cost-Benefit Dashboards 99

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. You can use this during the data ingestion phase of the POC. Additionally, document any assumptions you are making.

Testing 102

Testing Data Warehouse Metrics Cost-Benefit 102

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 100

Data Warehouse Testing Data Lake Data-driven 100

Jet Global

JANUARY 15, 2021

In the world of ERP software, switching costs include a number of hard costs like license fees, system analysis and design, customization, third-party add-ons, report design, and more, but many of those tasks also consume valuable staff time and management attention. Reporting as a Key Cost-driver.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

AWS Big Data

JUNE 28, 2023

When data is used to improve customer experiences and drive innovation, it can lead to business growth. times more likely than beginners to report at least 20% revenue growth. However, to realize this growth, managing and preparing the data for analysis has to get easier.

Analytics 71

Analytics Data Warehouse Data Lake Data-driven 71

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. That Was Then. This is Now.

Data Warehouse 91

Data Warehouse Machine Learning Visualization Data Lake 91

Jet Global

OCTOBER 30, 2020

As you do, it’s important to understand some important technical changes that could impact your ability to get information out of the system. For leaders in the finance and accounting department, it can often be frustrating to have conversations with IT experts about your reporting needs. Reporting: A Few Technical Basics.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

erwin

SEPTEMBER 3, 2020

Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change. Data governance provides time-sensitive, current-state architecture information with a high level of quality.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

BizAcuity

MAY 16, 2022

In brief, business intelligence is about how well you leverage, manage and analyze business data. When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. When information is at your fingertips, the possibilities are endless.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

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

Cloudera

OCTOBER 6, 2022

For example, we have some customers using their data platform originally established for compliance initiatives to drive new use cases. These data lakes house much of the data needed to also support other use cases. We maintain the same information in multiple places because it is used across the enterprise.

Digital Transformation 84

Digital Transformation Cost-Benefit Data Lake Machine Learning 84

IBM Big Data Hub

OCTOBER 16, 2023

Most of today’s largest foundation models, including the large language model (LLM) powering ChatGPT, have been trained on information culled from the internet. But how trustworthy is that training data? Capture and document model metadata for report generation. Trustworthiness is critical. Increase trust in AI outcomes.

Risk 73

Risk Modeling Management Metadata 73

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

Jet Global

JANUARY 18, 2021

Rather, they must consider how these changes might impact their workflows, user training, reports, customizations, and third-party products. Customizations, third-party software products, and reporting require particular attention in their own right, not just as they relate to removed or deprecated features.

Data Lake 98

Data Lake Reporting Cost-Benefit Finance 98

Domino Data Lab

JANUARY 11, 2021

Arming data science teams with the access and capabilities needed to establish a two-way flow of information is one critical challenge many organizations face when it comes to unlocking value from their modeling efforts. Retrieving information from Snowflake to work with in Domino. Introduction. link] becomes “test.eu-west-1”

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

Andrew White

DECEMBER 9, 2019

The outline of the call went as follows: I was taking to a central state agency who was organizing a data governance initiative (in their words) across three other state agencies. All four agencies had reported an independent but identical experience with data governance in the past. The information artifacts in scope.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

CIO Business Intelligence

DECEMBER 1, 2022

Now halfway into its five-year digital transformation, PepsiCo has checked off many important boxes — including employee buy-in, Kanioura says, “because one way or another every associate in every plant, data center, data warehouse, and store are using a derivative of this transformation.” billion in revenue.

Digital Transformation 139

Digital Transformation IoT Data-driven KPI 139

Alation

FEBRUARY 20, 2020

Tools like MicroStrategy and Tableau make it easy for business users to quickly turn raw data into visualizations and reports. But before you can even start, you have to find a relevant data set, understand it, and trust it. Complete MicroStrategy Data & Report Cataloging. abc/xyz, etc.).

Reporting 52

Reporting Dashboards Data Governance Visualization 52

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. Limited self-service reporting across the enterprise.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. Integrating data across this hybrid ecosystem can be time consuming and expensive. The volume of data assets.

Data-driven 57

Data-driven Enterprise Data Governance Data Lake 57

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

Sisense

APRIL 26, 2020

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. Different types of information are more suited to being stored in a structured or unstructured format. Structured vs unstructured data.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 79

Data Lake Data Warehouse Sales Data-driven 79