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.

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Optimization B2B Data Quality Sales 92

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. 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

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 Data Warehouse Predictive Analytics 40

DataKitchen

SEPTEMBER 21, 2023

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. What is Data in Use?

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Testing Data Quality Predictive Modeling Metrics 169

datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

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Business Intelligence Data Warehouse Data Processing Data mining 292

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 102

Data Lake Unstructured Data Data Warehouse Data Quality 102

CIO Business Intelligence

NOVEMBER 7, 2023

Centralized reporting boosts data value For more than a decade, pediatric health system Phoenix Children’s has operated a data warehouse containing more than 120 separate data systems, providing the ability to connect data from disparate systems. Companies should also incorporate data discovery, Higginson says.

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Data Warehouse Digital Transformation Data-driven Reporting 139

CIO Business Intelligence

JANUARY 20, 2023

Blocking the move to a more AI-centric infrastructure, the survey noted, are concerns about cost and strategy plus overly complex existing data environments and infrastructure. Though experts agree on the difficulty of deploying new platforms across an enterprise, there are options for optimizing the value of AI and analytics projects. [2]

Analytics 129

Analytics Key Performance Indicator Unstructured Data IoT 129

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 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 Sales 52

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 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

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IT Statistics KPI Data-driven 317

IBM Big Data Hub

DECEMBER 7, 2023

This siloed approach often resulted in data redundancy and complexity, hampering integration with other business systems. C-OLAP optimized data storage for faster query processing, while IM-OLAP stored data in memory to minimize data access latency and enable real-time analytics.

OLAP 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

BI-Survey

FEBRUARY 17, 2020

With the growing interconnectedness of people, companies and devices, we are now accumulating increasing amounts of data from a growing variety of channels. New data (or combinations of data) enable innovative use cases and assist in optimizing internal processes. However, effectively using data needs to be learned.

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Data Governance Data Warehouse Data Quality Data Strategy 89

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 96

Analytics Key Performance Indicator Data Warehouse Data-driven 96

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

CIO Business Intelligence

JULY 28, 2023

Enterprises are dealing with increasing amounts of data, and managing it has become imperative to optimize its value and keep it secure. Data lifecycle management is essential to ensure it is managed effectively from creation, storage, use, sharing, and archive to the end of life when it is deleted.

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Risk Management Cost-Benefit Data mining 80

IBM Big Data Hub

OCTOBER 27, 2022

Lindt now has a team of 10, including a business intelligence (BI) manager and BI developer analysts. Consequently, this data was siloed, unshareable, hard to use, lacked quality and governance controls, and could not be used in automated processes.

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Slice and Dice Analytics Sales Business Analytics 52

CIO Business Intelligence

MARCH 9, 2022

Data-driven organizations understand that data, when analyzed, is a strategic asset. It forms the basis for making informed decisions around product innovation, dynamic pricing, market expansion, and supply chain optimization. Ready to evolve your analytics strategy or improve your data quality?

Data-driven 88

Data-driven Analytics Machine Learning Optimization 88

CIO Business Intelligence

MAY 23, 2024

More recently, products have become increasingly digital, with software that manages patient flows, tools for surgery planning, and sterile management processes that optimize inventory and ensure that surgical instruments are delivered at the right time to the right place.

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Digital Transformation Measurement Cost-Benefit Data Warehouse 98

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. So, Alex and other business analysts could complete their projects faster.

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Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

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Analytics Data Warehouse Data Lake Metadata 74

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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Cost-Benefit Metadata Optimization Management 77

CIO Business Intelligence

NOVEMBER 22, 2022

The next step in every organization’s data strategy, Guan says, should be investing in and leveraging artificial intelligence and machine learning to unlock more value out of their data. CIOs should first understand the different approaches to observing data and how it differs from quality management,” he notes.

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Data Strategy Strategy Enterprise Consulting 145

IBM Big Data Hub

OCTOBER 12, 2023

To maximize the business outcomes that can come from using AI while also controlling costs and reducing inherent AI complexities, organizations need to combine AI-optimized data storage capabilities with a data governance program exclusively made for AI. But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 78

Cost-Benefit Metadata Data Governance Modeling 78

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

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Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Poor data quality.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

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 108

Cost-Benefit Internet of Things Data-driven Data Lake 108

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

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 122

Analytics Data Science Statistics Unstructured Data 122

CIO Business Intelligence

NOVEMBER 29, 2022

Layering technology on the overall data architecture introduces more complexity. Today, data architecture challenges and integration complexity impact the speed of innovation, data quality, data security, data governance, and just about anything important around generating value from data.

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Data Architecture Data Integration IoT Strategy 99

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

Alation

SEPTEMBER 7, 2021

Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. But governance is a time-consuming process (for users and data stewards alike). Find Trusted Data. Two problems arise.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

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 124

Big Data Data Analytics Analytics Predictive Modeling 124

IBM Big Data Hub

AUGUST 4, 2023

Data fabric Data fabric architectures are designed to connect data platforms with the applications where users interact with information for simplified data access in an organization and self-service data consumption. MLOps creates a process where it’s easier to cull insights from business data.

Data Architecture 60

Data Architecture Data Lake Machine Learning Data Governance 60

FineReport

MAY 31, 2023

Furthermore, we will introduce some business intelligence solution that excels in simplifying the process of creating and utilizing a financial dashboard effectively. Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses.

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Dashboards Key Performance Indicator Metrics Visualization 52

AWS Big Data

APRIL 25, 2023

Looking for a tool that would enable us to democratize our data, we chose Amazon QuickSight , a cloud-native, serverless business intelligence (BI) service that powers interactive dashboards that lets us make better data-driven decisions, as a corporate solution for data visualization.

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Visualization IT Data-driven Reporting 52