CIO Business Intelligence

JANUARY 24, 2024

“Rather, structure data teams to be organizationally centralized [and] physically co-located with the business — with objectives aligned to that business.” This approach helps to establish a unified data ecosystem that enables seamless data integration, sharing, and collaboration across the organization, Swann says.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics includes the tools and techniques used to perform data analysis.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Dataiku

JUNE 26, 2019

Last year when we surveyed over one hundred data professionals, they ranked organizational change as their third biggest data challenge (behind data cleaning and model productionalization).

Data Integration 95

Data Integration Modeling Data Transformation 95

Ontotext

AUGUST 24, 2023

The solution is choosing one of the standard provenance models. Standard provenance models Graph Replace is probably the most straightforward model. Trade-offs of the standard provenance models Graph Replace is fast and simple to implement and we recommend it to people with batch updates.

Data Integration 52

Data Integration Modeling Business Objectives Optimization 52

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on.

Data Governance 40

Data Governance Risk Metadata Management 40

Cloudera

JUNE 1, 2021

This means we can double down on our strategy – continuing to win the Hybrid Data Cloud battle in the IT department AND building new, easy-to-use cloud solutions for the line of business. It also means we can complete our business transformation with the systems, processes and people that support a new operating model. .

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Enterprise 80

Enterprise Data Integration Data Quality Contextual Data 80

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. There Will Never Be One “Best” Data Transformation Pipeline Tool.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Sisense

AUGUST 6, 2020

As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data? When building your data model, it’s vital to avoid both underfitting and overfitting.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The serverless architecture features auto scaling, high availability, and a pay-as-you-go billing model to increase agility and optimize costs.

Visualization 96

Visualization Dashboards Data-driven Gap analysis 96

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers. That data then fills several database tables. It’s not just a fear of change.

Testing 130

Testing Data-driven Visualization Dashboards 130

AWS Big Data

JULY 25, 2023

Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver fast performance for even the most demanding and unpredictable workloads, and you pay only for what you use. For S3 Setting , select Use an existing S3 connection and enter your existing connection that you will configure separately.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Alation

OCTOBER 28, 2021

Healthcare is changing, and it all comes down to data. Leaders in healthcare seek to improve patient outcomes, meet changing business models (including value-based care ), and ensure compliance while creating better experiences. Data & analytics represents a major opportunity to tackle these challenges.

Data Governance 52

Data Governance Measurement Modeling Metrics 52

AWS Big Data

JULY 20, 2023

This data is then used by various applications for streaming analytics, business intelligence, and reporting. Amazon SageMaker is used to build, train, and deploy a range of ML models. This ensures that the data is suitable for training purposes. Additionally, SageMaker training jobs are employed for training the models.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

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

AWS Big Data

NOVEMBER 7, 2023

For these, AWS Glue provides fast, scalable data transformation. Third, AWS continues adding support for more data sources including connections to software as a service (SaaS) applications, on-premises applications, and other clouds so organizations can act on their data. Visit Data integration with AWS to learn more.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

AWS Big Data

MARCH 15, 2023

The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption. To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

Cost-Benefit 66

Cost-Benefit Data Processing Optimization Data-driven 66

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Does Data Virtualization support web data integration?

Visualization 133

Visualization Cost-Benefit Big Data Prescriptive Analytics 133

Occam's Razor

OCTOBER 19, 2010

You simply cannot survive in this world with a clickstream mental model. I am forgetting the other 25 features these tools provide for free. I had promised tools and you got tools! Perhaps more than you cared for. But do remember three very very important things: 1. You have to embrace Web Analytics 2.0

Analytics 135

Analytics Testing Measurement Optimization 135

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Cost-effective pricing and comprehensive supporting services, maximizing value.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

CIO Business Intelligence

JANUARY 24, 2024

Exhibit 2 – Harnessing Collective Intelligence: Exploring Architectural Models in Agent Swarm Automation Supplied High-level layer-based architecture for Business Process Automation Decisions about how software is structured can greatly impact how it works and evolves over time. AI, ML Decision-Making Layer Make decisions based on insights.

IoT 117

IoT Machine Learning Optimization Internet of Things 117

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. As a result, alternative data integration technologies (e.g.,

Data Processing 88

Data Processing Data Warehouse Enterprise Visualization 88

DataKitchen

JANUARY 23, 2023

Testing data and analytic systems require a development system with accurate test data, tools, and relevant tool code. Only then can you tell the true impact of a column name change on the data transformations, the models, and the visualization you give to your customers.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

AUGUST 24, 2023

Although many companies run their own on-premises servers to maintain IT infrastructure, nearly half of organizations already store data on the public cloud. The Harvard Business Review study finds that 88% of organizations that already have a hybrid model in place see themselves maintaining the same strategy into the future.

Finance 52

Finance Reporting Data Integration Risk 52

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. Some cloud applications can even provide new benchmarks based on customer data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MARCH 14, 2024

Mastering Data: Effectively Manage Your Data Download Now How Jet Analytics Enhances Microsoft Fabric Jet Analytics from insightsoftware is a complete data preparation, automation and modeling solution that enables Microsoft Dynamics customers to accelerate Dynamics ERP-ready BI projects without requiring specialist skills.

Analytics 52

Analytics Management Reporting Enterprise 52

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting. With Atlas, you can put your data security concerns to rest.

Reporting 52

Reporting Finance Data Quality Sales 52

Jet Global

NOVEMBER 7, 2023

A complete data warehouse—without the heavy lifting: Automate the entire data warehousing process, from data retrieval through data transformation to deployment and generation of project documentation.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52