AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing.

Analytics 112

Analytics Data-driven Data Integration Data Lake 112

AWS Big Data

JANUARY 6, 2025

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

Analytics 97

Analytics Data Warehouse Metrics Big Data 97

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? What are the transformation rules? Collaboration.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

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. Azure Blob Storage serves as the data lake to store raw data.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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 and data science are closely related.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

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. Multi-channel publishing of data services. Does Data Virtualization support web data integration?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

AWS Big Data

JANUARY 30, 2025

AWS Glue A data integration service, AWS Glue consolidates major data integration capabilities into a single service. These include data discovery, modern ETL, cleansing, transforming, and centralized cataloging. Its also serverless, which means theres no infrastructure to manage.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 52

AWS Big Data

NOVEMBER 13, 2023

As Gameskraft’s portfolio of gaming products increased, it led to an approximate five-times growth of dedicated data analytics and data science teams. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

Data Warehouse 108

Data Warehouse Analytics Data Lake Data Science 108

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 105

Metadata Data Lake Visualization Data Quality 105

CIO Business Intelligence

JANUARY 24, 2024

With nearly 800 locations, RaceTrac handles a substantial volume of data, encompassing 260 million transactions annually, alongside data feeds from store cameras and internet of things (IoT) devices embedded in fuel pumps. This empowers data users to make decisions informed by data and in real-time with increased confidence.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

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

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. This connector provides comprehensive access to SFTP storage, facilitating cloud ETL processes for operational reporting, backup and disaster recovery, data governance, and more.

Data Processing 104

Data Processing Visualization Data Lake Data Processing 104

Wayne Yaddow

MARCH 3, 2025

These strategies minimize risks, streamline deployment processes, and future-proof data transformations, allowing businesses to trust their data before it ever reaches production. Helps maintain business rule consistency and avoid regressions in data quality overtime. Summary: Why thisorder?

Data Quality 52

Data Quality Strategy ROI Testing 52

DataKitchen

DECEMBER 9, 2022

DataOps automation typically involves the use of tools and technologies to automate the various steps of the data analytics and machine learning process, from data preparation and cleaning, to model training and deployment. The data scientists and IT professionals were amazed, and they couldn’t believe their eyes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

Occam's Razor

OCTOBER 19, 2010

I consider it my business as a web analyst, to report on how well the site is being indexed, keywords it is showing up for (but not getting clicks for), changes in trends for impression share and clicks on search engines (via the brand spanking new Google Webmaster Tools report) etc. of these three tools: ~ Yahoo! You may not.

Analytics 136

Analytics Testing Measurement Optimization 136

Ontotext

MARCH 20, 2024

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Unleashing the Power of Data Connections Zenia Graph isn’t just another data solution company.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

AWS Big Data

MARCH 3, 2023

Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights. Each of these tools has its own reporting capabilities that make it difficult to combine the data for integrated and actionable business insights. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

FineReport

JUNE 7, 2024

With a focus on innovation and client-centricity, FanRuan’s key features encompass dynamic visualizations, interactive dashboards , and seamless integration capabilities. Elevate your data transformation journey with Dataiku’s comprehensive suite of solutions.

Visualization 52

Visualization Predictive Analytics Dashboards Predictive Modeling 52

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 Science Data Transformation 52

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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

JULY 20, 2023

This data is then used by various applications for streaming analytics, business intelligence, and reporting. This functionality has proven to be extremely useful in identifying potential data quality issues and swiftly resolving them by reverting to a previous state with known data integrity.

Data Lake 96

Data Lake Analytics Snapshot Data Quality 96

Alation

OCTOBER 28, 2021

Whether they want to steal identities, sell data, or hold information hostage, these actors recognize that such data has a financial value. The 2021 Data Breach Investigations Report found that in healthcare: 61% of data breaches were caused by external actors. 91% of data breaches were financially motivated.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

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 119

Data Lake Management Metrics Data Warehouse 119

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

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

FineReport

MARCH 31, 2024

These tools empower organizations to glean valuable insights from their data, enhancing decision-making processes and bolstering competitiveness in data-driven markets. These tools seamlessly connect and consolidate data from diverse sources, ensuring cleanliness, structure, and aggregation of data in various formats.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Smarten

JANUARY 4, 2018

Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40

erwin

MARCH 26, 2020

David Loshin explores this concept in an erwin-sponsored whitepaper, Data Intelligence: Empowering the Citizen Analyst with Democratized Data. In the whitepaper he states, the priority of the citizen analyst is straightforward: find the right data to develop reports and analyses that support a larger business case.

Data-driven 90

Data-driven Unstructured Data Enterprise Machine Learning 90

DataKitchen

JANUARY 23, 2023

For example, a data error may only be apparent when combined with other data or used in a specific analysis or report. Additionally, data lineage may not capture the impact of data errors on downstream systems or processes. Which report tab is wrong? Which production job filled that report?

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

MAY 1, 2023

But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint. These reports are critical to making decisions.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. 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

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 Visualization 52

Jet Global

MAY 6, 2024

Despite the transformative potential of AI, a large number of finance teams are hesitating, waiting for this emerging technology to mature before investing. According to a recent Gartner report, a staggering 61% of finance organizations haven’t yet adopted AI. This eliminates data fragmentation, a major obstacle for AI.

Finance 52

Finance Reporting Data Transformation Data-driven 52

Jet Global

AUGUST 24, 2023

Given your organizations focus on productivity, you know soon your team will working in a divided reporting environment. While the cloud infrastructure promises to bring positive changes, your company’s data will exist in both worlds: on-prem and the cloud.

Finance 52

Finance Reporting Data Integration Data Warehouse 52

Jet Global

NOVEMBER 7, 2023

When extracting your financial and operational reporting data from a cloud ERP, your enterprise organization needs accurate, cost-efficient, user-friendly insights into that data. While real-time extraction is historically faster, your team needs the reliability of the replication process for your cloud data extraction.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

Jet Global

JULY 16, 2024

Imagine trying to analyze data with a constantly changing backend—it’s like kicking the legs out from underneath a table and still expecting it to stay upright. Your dashboards and reports need a stable foundation for your data to work correctly! What is Apache Iceberg?

Dashboards 52

Dashboards Data-driven Reporting Business Intelligence 52

Jet Global

MARCH 13, 2024

Between complex data structures, data security questions, and error-prone manual processes, merging data from disparate sources into a single system can quickly turn your routine reporting processes into a stressful and time-consuming ordeal. With Atlas, you can put your data security concerns to rest.

Reporting 52

Reporting Finance Data Quality Sales 52