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. Amazon Web Services.

Management 99

Management Data Warehouse Digital Transformation Dashboards 99

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. usr/local/airflow/.local/bin/dbt

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. The data warehouse is highly business critical with minimal allowable downtime. Data engineers are crucial for schema conversion and data transformation, and DBAs can handle cluster configuration and workload monitoring.

Data Warehouse 114

Data Warehouse KPI Optimization Cost-Benefit 114

Sisense

OCTOBER 15, 2020

Every data professional knows that ensuring data quality is vital to producing usable query results. Streaming data can be extra challenging in this regard, as it tends to be “dirty,” with new fields that are added without warning and frequent mistakes in the data collection process. Step 4: Query.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

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

DECEMBER 21, 2023

AWS Glue provides both visual and code-based interfaces to make data integration effortless. Using a native AWS Glue connector increases agility, simplifies data movement, and improves data quality. Choose the link under OpenSearch Dashboards URL. Choose Dashboards Management on the navigation menu.

Analytics 110

Analytics IT Data Lake Visualization 110

Jen Stirrup

SEPTEMBER 30, 2021

Before we dive in, let’s define strands of AI, Machine Learning and Data Science: Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

Octopai

JUNE 9, 2024

The goal was to develop sophisticated data products, such as predictive analytics models to forecast patient needs, patient care optimization tools, and operational efficiency dashboards. These data products were intended to enhance patient outcomes, streamline hospital operations, and provide actionable insights for decision-making.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

AWS Big Data

APRIL 5, 2023

Showpad built new customer-facing embedded dashboards within Showpad eOSTM and migrated its legacy dashboards to Amazon QuickSight , a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

MAY 28, 2019

A data warehouse is typically used by companies with a high level of data diversity or analytical requirements. As the complexity and volume of data used in the enterprise scales and organizations want to get more out of their analytics efforts, data warehouses are gaining more traction for reporting and analytics over databases.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

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

To make good on this potential, healthcare organizations need to understand their data and how they can use it. These systems should collectively maintain data quality, integrity, and security, so the organization can use data effectively and efficiently. Why Is Data Governance in Healthcare Important?

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 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.

Reporting 52

Reporting Finance Data Quality Sales 52

Jet Global

AUGUST 24, 2023

It streamlines data integration, ensures real-time access to accurate information, enhances collaboration, and provides the flexibility needed to adapt to evolving ERP systems and business requirements. Data transformation ensures that the data aligns with the requirements of the new cloud ERP system.

Finance 52

Finance Reporting Data Integration Data Warehouse 52

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. However, our initial data architecture led to challenges.

Data Transformation 55

Data Transformation Cost-Benefit Testing Data Lake 55