datapine

MAY 2, 2023

The rise of SaaS business intelligence tools is answering that need, providing a dynamic vessel for presenting and interacting with essential insights in a way that is digestible and accessible. The future is bright for logistics companies that are willing to take advantage of big data. Now’s the time to strike.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

Wayne Yaddow

FEBRUARY 26, 2025

AI is transforming how senior data engineers and data scientists validate data transformations and conversions. Artificial intelligence-based verification approaches aid in the detection of anomalies, the enforcement of data integrity, and the optimization of pipelines for improved efficiency.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

datapine

SEPTEMBER 29, 2022

Therefore, there are several roles that need to be filled, including: DQM Program Manager: The program manager role should be filled by a high-level leader who accepts the responsibility of general oversight for business intelligence initiatives. The program manager should lead the vision for quality data and ROI.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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? In business analytics, this is the purview of business intelligence (BI).

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

CIO Business Intelligence

JULY 5, 2022

Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. What is the difference between business analytics and business intelligence?

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

CIO Business Intelligence

DECEMBER 9, 2024

For now, 51% say this strategic alignment has not been fully achieved, according to NTT DATAs study. [3] Data readiness and governance are critical to success and must be addressed in tandem with business process transformation. 3] Preparation. Operations.

Technology 98

Technology Insurance Interactive Reporting 98

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Let’s take a common use-case for Business Intelligence reporting. Figure 2: Example BI reporting data pipeline.

Management 115

Management Cost-Benefit Data Transformation Optimization 115

Octopai

MARCH 31, 2021

In other words, kind of like Hansel and Gretel in the forest, your data leaves a trail of breadcrumbs – the metadata – to record where it came from and who it really is. So the first step in any data lineage mapping project is to ensure that all of your data transformation processes do in fact accurately record metadata.

Metadata 133

Metadata Data Transformation Business Intelligence Reporting 133

AWS Big Data

JANUARY 15, 2025

In this post, we show you how EUROGATE uses AWS services, including Amazon DataZone , to make data discoverable by data consumers across different business units so that they can innovate faster. We encourage you to read Amazon DataZone concepts and terminology to become familiar with the terms used in this post.

IoT 100

IoT Machine Learning Metadata Data-driven 100

CIO Business Intelligence

APRIL 30, 2024

Einstein Copilot for Tableau remains in beta, but Tableau announced two new features for the AI assistant as well: AI-assisted data transformation. This feature can automate a data transformation pipeline with step-by-step suggestions for preparing data for analysis.

Analytics 96

Analytics Metrics Visualization Dashboards 96

CIO Business Intelligence

FEBRUARY 27, 2025

Additionally, integrating mainframe data with the cloud enables enterprises to feed information into data lakes and data lake houses, which is ideal for authorized data professionals to easily leverage the best and most modern tools for analytics and forecasting. Four key challenges prevent them from doing so: 1.

Metadata 98

Metadata Data Lake Cost-Benefit Forecasting 98

Sisense

DECEMBER 12, 2019

Here’s the crux of the problem: businesses have become masters at collecting data but are failing to invest in a business intelligence and data analytics solution to derive value from that data. Trying to fit your business intelligence cost into an existing budget is an uphill battle for many organizations.

Business Intelligence 88

Business Intelligence Software Data-driven Visualization 88

TDAN

FEBRUARY 21, 2024

In a world increasingly dominated by data, organizations are grappling with the need to effectively manage and harness this valuable asset.

Data Transformation 59

Data Transformation Digital Transformation Data-driven Management 59

AWS Big Data

NOVEMBER 27, 2024

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, business intelligence (BI), and reporting tools. dbt Cloud is a hosted service that helps data teams productionize dbt deployments.

Data Warehouse 93

Data Warehouse Analytics Testing Sales 93

CIO Business Intelligence

NOVEMBER 17, 2022

Data has become a top priority for businesses large and small, and while some companies have already established a digital strategy, many of them are just getting started. However, the ability to drive digital technology transformation is going to be the focus,” says Stephen Van Vreede, resume expert at IT Tech Exec.

Data Governance 128

Data Governance Data Transformation Strategy Reporting 128

AWS Big Data

DECEMBER 16, 2024

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. The product data is stored on Amazon Aurora PostgreSQL-Compatible Edition.

Visualization 71

Visualization Data Processing Testing Publishing 71

AWS Big Data

JANUARY 30, 2025

Diagram 1: Overall architecture of the solution, using AWS Step Functions, Amazon Redshift and Amazon S3 The following AWS services were used to shape our new ETL architecture: Amazon Redshift A fully managed, petabyte-scale data warehouse service in the cloud. The following Diagram 2 shows this workflow.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 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. The reason Azure has so many analytics services is so you can build your entire stack there. Microsoft.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

CIO Business Intelligence

JANUARY 8, 2025

Secure storage, together with data transformation, monitoring, auditing, and a compliance layer, increase the complexity of the system. Security appliances and policies also need to be defined and configured to ensure that access is allowed only to qualified people and services.

Data Processing 139

Data Processing Optimization Modeling Enterprise 139

Jet Global

MAY 28, 2019

Unlike a database, a data warehouse’s architecture is built for getting the data out, and not just through technical expertise, but for common users like management, executives, finance professionals, and other staff. A data warehouse is typically used by companies with a high level of data diversity or analytical requirements.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

TDAN

JUNE 15, 2021

We have seen an impressive amount of hype and hoopla about “data as an asset” over the past few years. And one of the side effects of the COVID-19 pandemic has been an acceleration of data transformation in organisations of all sizes.

Data Transformation 98

Data Transformation Management Risk Management Risk 98

TDAN

DECEMBER 3, 2019

Everyone’s talking about data. Data is the key to unlocking insight— the secret sauce that will help you get predictive, the fuel for business intelligence. The transformative potential in AI? It relies on data. The good news is that data has never […].

Business Intelligence 72

Business Intelligence Dashboards Reporting Data Architecture 72

AWS Big Data

DECEMBER 4, 2024

Let’s look at the key services that enable the federated platform to operate at scale: Data storage and processing: Apache Iceberg on Amazon Simple Storage Service (Amazon S3) offers an optimized way to store data assets and products and promotes interoperability across other services Amazon Redshift allows domain teams to create and manage fit-for-purpose (..)

Metadata 93

Metadata Data Governance Data Quality Data-driven 93

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 118

Data Warehouse Testing Data Quality Reporting 118

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

CIO Business Intelligence

APRIL 8, 2025

Build data validation rules directly into ingestion layers so that insufficient data is stopped at the gate and not detected after damage is done. Use lineage tooling to trace data from source to report. Understanding how data transforms and where it breaks is crucial for audibility and root-cause resolution.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

SEPTEMBER 5, 2024

Federated queries are useful for use cases where organizations want to combine data from their operational systems with data stored in Amazon Redshift. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 106

IoT Data Warehouse Cost-Benefit Reporting 106

Smart Data Collective

APRIL 29, 2020

The techniques for managing organisational data in a standardised approach that minimises inefficiency. Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation.

Management 97

Management Data Warehouse Digital Transformation Dashboards 97

CIO Business Intelligence

FEBRUARY 16, 2023

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 97

Enterprise Data Warehouse Reporting Metadata 97

CIO Business Intelligence

FEBRUARY 20, 2024

The data transformation imperative What Denso and other industry leaders realise is that for IT-OT convergence to be realised, and the benefits of AI unlocked, data transformation is vital. The company can also unify its knowledge base and promote search and information use that better meets its needs.

Data Architecture 98

Data Architecture Unstructured Data Manufacturing IT 98

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 116

Data Lake Management Metrics Data Warehouse 116

AWS Big Data

MAY 16, 2023

Different communication infrastructure types such as mesh network and cellular can be used to send load information on a pre-defined schedule or event data in real time to the backend servers residing in the utility UDN (Utility Data Network). Karthik Tharmarajan is a Senior Specialist Solutions Architect for Amazon QuickSight.

Dashboards 85

Dashboards Statistics Data Collection Business Intelligence 85

AWS Big Data

APRIL 11, 2023

ElastiCache manages the real-time application data caching, allowing your customers to experience microsecond response times while supporting high-throughput handling of hundreds of millions of operations per second. In the inventory management and forecasting solution, AWS Glue is recommended for data transformation.

Forecasting 83

Forecasting Management IoT Data-driven 83

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Choose Update.

Data Lake 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

Smarten

AUGUST 13, 2024

There are numerous benefits and advantages to incorporating low-code, no-code into an analytical environment, and these benefits provide support for developers, data scientists and for power business users.

Analytics 59

Analytics Cost-Benefit Predictive Modeling Dashboards 59