AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. From an operational standpoint, we designed a new shared responsibility model for data ingestion using AWS Glue instead of internal services (REST APIs) designed on Amazon EC2 to extract the data.

Optimization 52

Optimization Forecasting Data Lake Metadata 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. ETL helps collect, optimize, and store data for better reporting and real-time analysis.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

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 81

Data Warehouse Cost-Benefit Metadata Data-driven 81

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.

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

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.

Unstructured Data 103

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 103

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. Comprehensive search and access to relevant data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Jet Global

OCTOBER 26, 2023

If your finance team is using JD Edwards (JDE) and Oracle E-Business Suite (EBS), it’s like they rely on well-maintained and accurate master data to drive meaningful insights through reporting. For these teams, data quality is critical. Ensuring that data is integrated seamlessly for reporting purposes can be a daunting task.

Data Quality 52

Data Quality Reporting Operational Reporting Finance 52

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

Jet Global

AUGUST 24, 2023

Optimized Resource Allocation: Finance teams can strategically allocate resources in a hybrid ERP environment. This optimization leads to improved efficiency, reduced operational costs, and better resource utilization. Cost Optimization: The hybrid model allows finance teams to balance their expenses effectively.

Finance 52

Finance Reporting Data Integration Risk 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

FineReport

MAY 31, 2023

Contemporary dashboards surpass basic visualization and reporting by utilizing financial analytics to amalgamate diverse financial and accounting data, empowering analysts to delve further into the data and uncover valuable insights that can optimize cost-efficiency and enhance profitability.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Cloudera

MAY 16, 2019

The conference provides a useful opportunity to reflect on the rapid evolution we’ve seen in the Data Integration and Management space, much of it driven by the innovations that Cloudera and the open source community have been delivering. The traditional Data Warehouse ETL process has splintered into many smaller components.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

datapine

FEBRUARY 22, 2022

IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. We love that data is moving permanently into the C-Suite. This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Because it is that important.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

AWS Big Data

APRIL 25, 2023

At Dafiti, the entire infrastructure is on AWS, and we use Amazon Redshift as our Data Warehouse. QuickSight, when using SPICE (Super-fast, Parallel, In-memory Calculation Engine), extracts data from Amazon Redshift as efficiently as possible using UNLOAD , which optimizes the use of Amazon Redshift.

Visualization 52

Visualization IT Data-driven Reporting 52

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. For many organizations, however, the question remains, “Is it the right solution for us?”

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Jet Global

JANUARY 13, 2023

KPIs such as efficiency, reducing stock levels, and optimizing logistics costs can conflict with your ambition to deliver on time. Furthermore, large data volumes and the intricacy of SAP data structures can add to your woes. Discover how SAP data quality can hurt your OTIF. Analyze your OTIF.

Measurement 52

Measurement Reporting Operational Reporting Forecasting 52

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. Layering technology on the overall data architecture introduces more complexity. For data warehouses, it can be a wide column analytical table.

Data Architecture 101

Data Architecture Data Integration IoT Strategy 101

Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

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 83

Cost-Benefit Metadata Data Governance Modeling 83

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 99

Analytics Key Performance Indicator Data Warehouse Data-driven 99

Alation

JANUARY 25, 2022

Just like Gartner, we’re confident building out this capability will optimize productivity, business optimization, and user experience. The data catalog provides the foundational capabilities for this. The Data Catalog as a Business Foundation. Alation Data Catalog for the data fabric. Simply put?

Metadata 52

Metadata IT Metrics Data-driven 52

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.

Data Warehouse 140

Data Warehouse Digital Transformation Data-driven Reporting 140

Smart Data Collective

OCTOBER 13, 2021

Agile BI and Reporting, Single Customer View, Data Services, Web and Cloud Computing Integration are scenarios where Data Virtualization offers feasible and more efficient alternatives to traditional solutions. Does Data Virtualization support web data integration? In improving operational processes.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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. By recognizing data as a product, it creates greater incentive to properly manage data.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. Analytics can help a business improve customer relationships, optimize advertising campaigns, develop new products, and much more. As an organization embraces digital transformation , more data is available to inform decisions. Boost Revenue.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52