CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 122

Business Intelligence Data-driven Statistics Data Warehouse 122

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

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Users interested in visual exploration can do so using AWS Glue DataBrew.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

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

Octopai

NOVEMBER 28, 2019

Once upon a time, almost all data had one shape, and it was a rectangle. For data structures that followed the relational database model, which relate to each other by “primary keys” and “foreign keys,” this approach worked well, as long as different databases didn’t have to “talk” to each other, at least not directly.

Visualization 54

Visualization Metadata Data Warehouse Reporting 54

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. They can use their own toolsets or rely on provided blueprints to ingest the data from source systems.

Dashboards 93

Dashboards Analytics Metadata Optimization 93

Ontotext

AUGUST 22, 2023

Context: The Key to Making Data Useful It goes without saying that data without meaning can yield incorrect insights, leading to potentially dangerous decisions. Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

NOVEMBER 29, 2023

This includes tools to help you customize your foundation models, and new services and features to build a strong data foundation to fuel your generative AI applications. Customizing foundation models The need for data is quite obvious if you are building your own foundation models (FMs).

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

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 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

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

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

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 70

Analytics Data Warehouse Data Lake Metadata 70

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

Experimentation 81

Experimentation Data Warehouse Dashboards Visualization 81

Jet Global

DECEMBER 1, 2020

Finance teams often work with business intelligence (BI) tools to analyze data, identify trends, pinpoint discrepancies, and build informative, compelling reports for management. In addition, it can be very helpful to have a metadata layer in place that can help non-developers make sense of the information in the database.

Finance 78

Finance Data Warehouse OLAP Reporting 78

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 87

Data Lake Data Warehouse Data-driven B2B 87

Cloudera

SEPTEMBER 29, 2022

They are being bombarded with literature about seemingly independent new trends like data mesh and data fabric while dealing with the reality of having to work with hybrid architectures. Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem.

Data Architecture 74

Data Architecture Metadata Data Warehouse Sales 74

Octopai

APRIL 4, 2022

When you need to keep careful track of what’s happening to your data, data lineage for healthcare is your ally. Data lineage maps out the journey of any data asset or data point based on the metadata in healthcare systems. It’s here that automated data lineage can be a lifesaver. .

Metadata 92

Metadata Reporting Visualization Insurance 92

Octopai

OCTOBER 20, 2021

Octopai, the leader in automated data lineage, data catalog and data discovery, announced today its support and analysis of Amazon Redshift, one of the fastest and most widely used cloud data warehouses. By getting the full picture of what and how different tables, columns etc.

Metadata 52

Metadata Data Warehouse Enterprise Business Intelligence 52

AWS Big Data

JULY 28, 2023

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tags provide metadata about resources at a glance.

Snapshot 81

Snapshot Metadata Measurement Data Warehouse 81

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Technical metadata to describe schemas, indexes and other database objects.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business.

Data Quality 241

Data Quality Metrics Data-driven Management 241

FineReport

MAY 6, 2020

Metode statistik yang berkaitan dengan data mining: analisis regresi logistik multi variasi, analisis regresi non linear, analisis diskriminan, dll. Metode kuantitatif: analisis axis waktu, model probabilitas, optimalisasi. Prinsip database: model data, desain database. Data Warehouse.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 98

Octopai

NOVEMBER 24, 2021

As the first of its reasons why to migrate to Redshift , Amazon says, “Amazon Redshift is fully managed and simple to use, enabling you to deploy a new data warehouse in minutes and load virtually any type of data from a range of cloud or on-premises data sources.”. Setting up the data warehouse can take minutes.

Data Warehouse 73

Data Warehouse Metadata Data Processing Reporting 73

AWS Big Data

FEBRUARY 1, 2023

The response times for these data sources are critical to our key stakeholders. Therefore, we must take a data-driven approach to select a high-performance architecture. Storage and redundancy – Due to the heterogeneous data stores and models, it was challenging to store the different datasets from various business stakeholder teams.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly. MDM Model Objects.

Management 52

Management Data Quality Metadata Testing 52

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

Andrew White

OCTOBER 22, 2021

Monetization/Link data to outcome (value pyramid) business value of data/business impact 20. Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13. Data Management Infrastructure/Data Fabric 5.

IT 52

IT Data Lake Strategy Data Science 52

AWS Big Data

MARCH 9, 2023

Thousands of customers rely on Amazon Redshift to build data warehouses to accelerate time to insights with fast, simple, and secure analytics at scale and analyze data from terabytes to petabytes by running complex analytical queries. The star schema is a popular data model for building data marts.

Slice and Dice 80

Slice and Dice Data Warehouse Metrics Metadata 80

Ontotext

MARCH 8, 2023

With the size of data and dropping attention spans of online users, digital personalization has become one of the top priorities for companies’ business models. As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

AUGUST 1, 2023

For GlueDatabaseName , enter a unique name for the Data Catalog database to hold the Jira data table metadata (the default is jiralake ). This mode will scan all data and disable the change data capture (CDC) features of the stack. For InitialRunFlag , choose Setup. About the Authors Tom Romano is a Sr.

Data Lake 84

Data Lake Data Transformation Cost-Benefit Data-driven 84

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

erwin

SEPTEMBER 25, 2020

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. In this post: What Is a Data Model? Why Is Data Modeling Important?

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

CIO Business Intelligence

DECEMBER 21, 2022

BI software helps companies do just that by shepherding the right data into analytical reports and visualizations so that users can make informed decisions. To gain employee buy-in, Stout’s team builds BI dashboards to show them how they can easily connect to and interact with their data, as well as visualize it in a meaningful way.

IT 126

IT Business Intelligence Sales Key Performance Indicator 126

IBM Big Data Hub

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. New insights and relationships are found in this combination. All of this supports the use of AI.

Data Lake 83

Data Lake Metadata Cost-Benefit Data Warehouse 83