datapine

SEPTEMBER 27, 2022

The all-encompassing nature of this book makes it a must for a data bookshelf. 18) “The Data Warehouse Toolkit” By Ralph Kimball and Margy Ross. It is a must-read for understanding data warehouse design. 6) “SQL: QuickStart Guide – The Simplified Beginner’s Guide To SQL” By Clydebank Technology. Viescas, Douglas J.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

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 173

Testing Data Quality Predictive Modeling Metrics 173

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. Implement data privacy policies. Implement data quality by data type and source.

Data Governance 124

Data Governance Unstructured Data Metadata Data Lake 124

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

FEBRUARY 27, 2024

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.

Data-driven 111

Data-driven Data Lake Data Quality Data Governance 111

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage).

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Jet Global

JANUARY 20, 2021

As the volume of available information continues to grow, data management will become an increasingly important factor in effective business management. Lack of proactive data management, on the other hand, can result in incompatible or inconsistent sources of information, as well as data quality problems.

Data Analytics 95

Data Analytics Management Analytics Data Warehouse 95

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. dbt emerged as the perfect choice for this transformation within their existing AWS environment.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

AWS Big Data

MARCH 26, 2024

Customer 360 (C360) provides a complete and unified view of a customer’s interactions and behavior across all touchpoints and channels. This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. Then, you transform this data into a concise format.

Data Strategy 103

Data Strategy Strategy Data Warehouse Prescriptive Analytics 103

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 97

Analytics Data Warehouse Data Lake Metadata 97

datapine

FEBRUARY 22, 2022

This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

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

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 111

Enterprise Data Warehouse Snapshot Cost-Benefit 111

DataKitchen

JANUARY 19, 2022

DataKitchen acts as a process hub that unifies tools and pipelines across teams, tools and data centers. DataKitchen could, for example, provide the scaffolding upon which a Snowflake cloud data platform or data warehouse could be integrated into a heterogeneous data mesh domain.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

Octopai

JULY 12, 2020

After all, how do you adjust this month’s operations based on last month’s data if it takes two weeks to finally receive the information you need? This is exactly how Octopai customer, Farm Credit Services of America (FCSA) , felt when their BI team needed to modernize their data warehouse.

Data Warehouse 84

Data Warehouse Data Quality Metadata Risk Management 84

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

CIO Business Intelligence

DECEMBER 21, 2022

“The number-one issue for our BI team is convincing people that business intelligence will help to make true data-driven decisions,” says Diana Stout, senior business analyst at Schellman, a global cybersecurity assessor based in Tampa, Fl. Or you have a [BI tool] like Domo, which Schellman uses, that can function as a data warehouse.

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

AWS Big Data

APRIL 4, 2024

Griffin is an open source data quality solution for big data, which supports both batch and streaming mode. In today’s data-driven landscape, where organizations deal with petabytes of data, the need for automated data validation frameworks has become increasingly critical.

Data Quality 90

Data Quality Data Lake Data Warehouse Data-driven 90

Laminar Security

DECEMBER 13, 2023

In the ever-evolving digital landscape, the importance of data discovery and classification can’t be overstated. As we generate and interact with unprecedented volumes of data, the task of accurately identifying, categorizing, and utilizing this information becomes increasingly difficult.

Data-driven 119

Data-driven Machine Learning Deep Learning Risk 119

AWS Big Data

FEBRUARY 13, 2023

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 96

Snapshot Data Warehouse Analytics Testing 96

erwin

FEBRUARY 28, 2019

It’s a direct result of the data-driven customer experiences that are increasingly the norm in the private sector. Residents want the ability to pay their taxes online, report a pothole from their phone, and generally make it easier to interact with their local officials and services.

Digital Transformation 106

Digital Transformation Data Governance Data-driven Data Warehouse 106

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

CIO Business Intelligence

JUNE 14, 2023

CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP. They know how to assess data quality and understand data security, including row-level security and data sensitivity.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Alation

FEBRUARY 20, 2020

In 2016, people will realize the importance of scaling the generation of insights in parallel with the data – and finally have the ability to manage sprawl and realize new levels of insights from the data. 2016 will be the year of the “logical data warehouse.” Subscribe to Alation's Blog.

Data Warehouse 52

Data Warehouse Visualization Data Science Enterprise 52

Cloudera

APRIL 1, 2024

It unifies structured data with unstructured data giving a holistic view of the business and enhancing the efficacy of AI by providing it with more structured and accessible business data as context. At Cloudera, we are embedding AI in all our products to improve productivity of data professionals.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

CIO Business Intelligence

FEBRUARY 14, 2023

This has also accelerated the execution of edge computing solutions so compute and real-time decisioning can be closer to where the data is generated. AI continues to transform customer engagements and interactions with chatbots that use predictive analytics for real-time conversations.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 98

Data Lake Data Governance Data Architecture Machine Learning 98

Wayne Yaddow

MARCH 14, 2025

Moreover, dbt Core enables users to implement business logic directly within transformations, thereby ensuring contract validation for regulatory compliance or data quality governancesuch as confirming that all high-value transactions include approval codes or that sensitive personal data remains obscured.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

Ontotext

FEBRUARY 12, 2024

It proposes a technological, architectural, and organizational approach to solving data management problems by breaking up the monolithic data platform and de-centralizing data management across different domain teams and services. Once these domains interact and share data with each other, the mesh emerges.

IT 64

IT Metadata Data Quality Data Lake 64

Alation

NOVEMBER 2, 2022

At Databricks, we’re focused on enabling customers to adopt the data lakehouse, and that’s an open data architecture that combines the best of the data warehouse and the data lake into one platform,” Ferguson says. “[The And data governance is critical to driving adoption.”.

Data Governance 98

Data Governance Marketing Finance Data Lake 98

Alation

FEBRUARY 7, 2023

It wouldn’t be until 2013 that the topic of data lineage would surface again – this time while working on a data warehouse project. Data warehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company. We finally had a useful tool. Or so I thought.

Metadata 52

Metadata Data Warehouse Visualization Data Quality 52

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

IBM Big Data Hub

AUGUST 4, 2023

Architecture for data democratization Data democratization requires a move away from traditional “data at rest” architecture, which is meant for storing static data. Traditionally, data was seen as information to be put on reserve, only called upon during customer interactions or executing a program.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

IBM Big Data Hub

JULY 27, 2023

Data quality strongly impacts the quality and usefulness of content produced by an AI model, underscoring the significance of addressing data challenges. Summarization can help employees by providing them a brief of the customer’s problem and previous interactions with the company.

Management 54

Management Enterprise Modeling Data Quality 54

erwin

FEBRUARY 28, 2024

Examples of complementary technologies include technology for data warehouse automation, change data capture and master data management. For data governance, it’s more complex. Finally, automated data quality scoring from erwin Data Quality is completely integrated within erwin Data Intelligence data lineage.

Metadata 52

Metadata Data Governance Data Quality Technology 52

AWS Big Data

DECEMBER 9, 2024

Equally crucial is the ability to segregate and audit problematic data, not just for maintaining data integrity, but also for regulatory compliance, error analysis, and potential data recovery. We discuss two common strategies to verify the quality of published data.

Data Quality 126

Data Quality Publishing Snapshot Data Lake 126

Alation

JANUARY 27, 2022

The proliferation of data sources means there is an increase in data volume that must be analyzed. Large volumes of data have led to the development of data lakes , data warehouses, and data management systems. Despite its immense value, a variety of data can create more work.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52