Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Jet Global

JULY 11, 2019

Although it’s been around for decades, predictive analytics is becoming more and more mainstream, with growing volumes of data and readily accessible software ripe for transforming. In this blog post, we are going to cover the role of business intelligence in demand forecasting, an area of predictive analytics focused on customer demand.

Business Intelligence 72

Business Intelligence Forecasting Predictive Analytics Data Warehouse 72

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Jet Global

JANUARY 17, 2019

In today’s data-driven world, business intelligence (BI) and analytics play a huge role in better understanding your customers, improving your operations, and making actionable business decisions. Take a look at the data you need to use in order to get any value from business intelligence and analytics.

Business Intelligence 75

Business Intelligence Management Data Warehouse Data Governance 75

CIO Business Intelligence

MAY 24, 2022

In order to help maintain data privacy while validating and standardizing data for use, the IDMC platform offers a Data Quality Accelerator for Crisis Response. Cloud Computing, Data Management, Financial Services Industry, Healthcare Industry

Finance 140

Finance Management Metadata Machine Learning 140

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 169

Testing Data Quality Predictive Modeling Metrics 169

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. What is ETL? Let’s break down each step: 1.

Data Quality 105

Data Quality Data Warehouse Data-driven Reporting 105

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. The data science and AI teams are able to explore and use new data sources as they become available through Amazon DataZone.

IoT 105

IoT Machine Learning Metadata Data-driven 105

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 101

Data Architecture Optimization Data Warehouse Metadata 101

Howard Dresner

JANUARY 4, 2015

I kicked off a recent discussion with this question to the group: “What are the top five worst practices in business intelligence?” I certainly don’t want to minimize the great successes organizations are having with business intelligence. It took only a few minutes for them to toss out a lot more than five.

Business Intelligence 45

Business Intelligence Recreation/Entertainment Sales Data Quality 45

AWS Big Data

DECEMBER 9, 2024

As organizations process vast amounts of data, maintaining an accurate historical record is crucial. History management in data systems is fundamental for compliance, business intelligence, data quality, and time-based analysis. Initialize the SparkSession with Iceberg settings.

Snapshot 64

Snapshot Data Warehouse Data Lake Data Quality 64

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.

Data Warehouse 105

Data Warehouse KPI Optimization Cost-Benefit 105

Jet Global

OCTOBER 1, 2019

Although it’s been around for decades, predictive analytics is becoming more and more mainstream, with growing volumes of data and readily accessible software ripe for transforming. In this blog post, we are going to cover the role of business intelligence in demand forecasting, an area of predictive analytics focused on customer demand.

Business Intelligence 40

Business Intelligence Forecasting Predictive Analytics Data Warehouse 40

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

David Menninger's Analyst Perspectives

OCTOBER 2, 2024

Data as a product is the process of applying product thinking to data initiatives to ensure that the outcome —the data product—is designed to be shared and reused for multiple use cases across the business. A data contract should also define data quality and service-level key performance indicators and commitments.

Key Performance Indicator 130

Key Performance Indicator Data Governance Data Warehouse Enterprise 130

CIO Business Intelligence

MARCH 22, 2022

One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Set up unified data governance rules and processes.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

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 122

Data Warehouse Testing Data Quality Reporting 122

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

Jet Global

FEBRUARY 5, 2019

It’s hard to answer that question because, truth be told, you don’t know you’re using bad data until it’s too late. . states that about 40 percent of enterprise data is either inaccurate, incomplete, or unavailable. Because bad data is the reason behind poor analytics. . Top 5 Warning Signs of Bad Data. Ted Friedman.

Data Warehouse 69

Data Warehouse Data Quality Business Intelligence Data Governance 69

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

DataKitchen

JANUARY 19, 2022

The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. DataKitchen acts as a process hub that unifies tools and pipelines across teams, tools and data centers.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

Octopai

JULY 12, 2020

GIGO may be an old refrain, but it likely gave rise to the concept of what we know as ‘business intelligence’. BI has helped enhance a company’s ability to process large amounts of data. Like many BI teams, FCSA’s struggles began with the massive amount of data that existed in their enterprise data warehouse.

Data Warehouse 84

Data Warehouse Data Quality Metadata Risk Management 84

AWS Big Data

JULY 13, 2023

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

Optimization 97

Optimization B2B Data Quality Sales 97

CIO Business Intelligence

NOVEMBER 22, 2022

External data sharing gets strategic Data sharing between business partners is becoming far easier and much more cooperative, observes Mike Bechtel, chief futurist at business advisory firm Deloitte Consulting. As such, you’re able to gain all the insights you need while avoiding having to overhaul your environment.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

DECEMBER 22, 2022

DataOps roles According to Goetz, DataOps team members include: Data specialists, who support the data landscape and development best practices Data engineers, who provide ad hoc and system support to BI, analytics, and business applications Principal data engineers, who are developers working on product and customer-facing deliverables DataOps salaries (..)

Analytics 130

Analytics Machine Learning Data mining Software 130

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ). Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

Management 98

Management Data Warehouse Digital Transformation Dashboards 98

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

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 102

Enterprise Data Warehouse Snapshot Cost-Benefit 102

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 84

Analytics Data Warehouse Data Lake Metadata 84

CIO Business Intelligence

MARCH 9, 2022

Some examples include: Customer 360 analytics, retail inventory and sales analysis, manufacturing operational analysis, eCommerce fraud prevention, network security intelligence, data warehouse consolidation and discount pricing optimization. Ready to evolve your analytics strategy or improve your data quality?

Data-driven 110

Data-driven Analytics Machine Learning Deep Learning 110

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