David Menninger's Analyst Perspectives

MARCH 17, 2022

Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance.

Business Intelligence 204

Business Intelligence Data Warehouse Data Quality Dashboards 204

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 75

Risk Modeling Management Metadata 75

CIO Business Intelligence

JUNE 24, 2022

Approximately 61% of APAC organizations have failed to build robust and successful digital business business models, primarily due to unsound practices of enterprise architecture (EA) teams, according to a report from Forrester. Digital Transformation

Modeling 105

Modeling Digital Transformation Data Architecture Data-driven 105

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 67

Data Warehouse Cost-Benefit Metadata Management 67

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. Amazon Redshift ML makes it easy for SQL users to create, train, and deploy ML models using SQL commands familiar to many roles such as executives, business analysts, and data analysts.

Modeling 64

Modeling Data Warehouse Machine Learning Testing 64

erwin

JULY 2, 2020

Users discuss how they are putting erwin’s data modeling, enterprise architecture, business process modeling, and data intelligences solutions to work. IT Central Station members using erwin solutions are realizing the benefits of enterprise modeling and data intelligence. This is live and dynamic.”.

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

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

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

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

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. Business intelligence analyst job requirements BI analysts typically handle analysis and data modeling design using data collected in a centralized data warehouse or multiple databases throughout the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

DataKitchen

AUGUST 19, 2021

Each data source is updated on its own schedule, for example, daily, weekly or monthly. The DataKitchen Platform ingests data into a data lake and runs Recipes to create a data warehouse leveraged by users and self-service data analysts. The third set of domains are cached data sets (e.g.,

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. From 2019 to now, Wang reports the amount of data the company holds has grown by a factor of 20.

Data Warehouse 115

Data Warehouse Cost-Benefit Sales Data-driven 115

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. 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

Octopai

APRIL 24, 2023

This new native integration enhances our data lineage solution by providing seamless integration with one of the most powerful cloud-based data warehouses, benefiting data teams and enabling support for a broader range of data lineage, discovery, and catalog.

Cost-Benefit 96

Cost-Benefit Data-driven Data Warehouse Data Governance 96

Jet Global

NOVEMBER 5, 2020

Reporting will change in D365 F&SCM, and those changes could significantly increase complexity and total cost of ownership. To enhance security, Microsoft has decided to restrict that kind of direct database access in D365 F&SCM and replace it with an abstraction layer comprised of something called “data entities”.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 144

Data mining Data-driven Statistics OLAP 144

Smart Data Collective

MAY 16, 2022

Data management systems provide a systematic approach to information storage and retrieval and help in streamlining the process of data collection, analysis, reporting, and dissemination. It also helps in providing visibility to data and thus enables the users to make informed decisions.

Management 127

Management Data mining Data Warehouse Data Collection 127

Cloudera

OCTOBER 4, 2023

On top of these core critical capabilities, we also need the following: Petabyte and larger scalability — particularly valuable in predictive analytics use cases where high granularity and deep histories are essential to training AI models to greater precision. Kudu has this covered. The post Don’t Blink: You’ll Miss Something Amazing!

Data Warehouse 83

Data Warehouse Experimentation Cost-Benefit Dashboards 83

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. The SQL query language used to extract data for reporting could also potentially be used to insert, update, or delete records from the database.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

CIO Business Intelligence

SEPTEMBER 12, 2022

Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. Fazal instructed his IT team to collect every bit of data and methodically determine its use later, rather than lose “precious” data in the rush to build a massive data warehouse. “We

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

O'Reilly on Data

AUGUST 18, 2020

We’ll share why in a moment, but first, we want to look at a historical perspective with what happened to data warehouses and data engineering platforms. Lessons Learned from Data Warehouse and Data Engineering Platforms. Data Science and Machine Learning Require Flexibility.

Data Science 355

Data Science Machine Learning Data Warehouse Deep Learning 355

erwin

SEPTEMBER 5, 2022

As with part 1 , part 2 ,and part 3 of this data modeling blog series, this blog also stresses that the cloud is not nirvana. Data modeling best practices. So, good relational design as covered in part 1 of this data modeling blog series holds true. Yes, it offers essentially infinitely scalable resources.

Modeling 52

Modeling Cost-Benefit Testing Data-driven 52

CIO Business Intelligence

MARCH 22, 2024

IBM said it would move to Rise in May 2022 while Microsoft gave a progress report on its own Rise migration in March that year. It began the process of standardizing 11 of its 55 ERP systems on SAP S/4HANA in 2019. Some of them are still running on ECC 6.0, the company’s spokeswoman wrote.

Data Processing 105

Data Processing Data Warehouse Management Software 105

CIO Business Intelligence

APRIL 10, 2019

BI analysts, with an average salary of $66,791 per year according to PayScale, provide application analysis and data modeling design for centralized data warehouses and extract data from databases and data warehouses for reporting, among other tasks. BI encompasses numerous roles.

Business Intelligence 111

Business Intelligence Data Warehouse Data-driven Software 111

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

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Athena provides a simplified, flexible way to analyze petabytes of data where it lives.

Data Lake 107

Data Lake Sales Data Warehouse Snapshot 107

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 109

Data Warehouse Testing Data Quality Reporting 109

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Cloudera Data Warehouse). Apache Hive.

Metrics 82

Metrics Slice and Dice Data Warehouse Dashboards 82

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. You pay only the associated Forecast costs. View Amazon Forecast pricing for details.

Forecasting 86

Forecasting Data Warehouse Machine Learning Modeling 86

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 90

Data Warehouse Machine Learning Visualization Data Lake 90

Jet Global

MARCH 25, 2020

While JD Edwards transactional data is required to run period close reports, analyze trends, and prepare forecasts for planning and budgeting, it comes with a lot of complexity. JD Edwards World has no less than 1600 tables of data to support just its business applications. 1 – What are all your reporting needs? .

Reporting 45

Reporting Finance Sales Visualization 45

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

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

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. Cost Cloud services operate on a pay-as-you-go model, and estimating costs accurately can be challenging during a POC.

Testing 102

Testing Data Warehouse Metrics Cost-Benefit 102

Cloudera

NOVEMBER 12, 2020

At these times, they run business growth reports, shareholder reports, and financial reports for their earnings calls, to name a few examples. Moving to a cloud-only based model allows for flexible provisioning, but the costs accrued for that strategy rapidly negate the advantage of flexibility. . A solution.

Data Warehouse 101

Data Warehouse Reporting Risk Cost-Benefit 101

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