Domo

MAY 7, 2021

Data repositories. Lots of data—structured and unstructured—gets dumped into data warehouses, lakes, and non-relational databases. These repositories often hold old records such as customer, employee, or financial data that must be kept for compliance reasons yet incur considerable storage costs.

Data Warehouse 98

Data Warehouse Documentation Retail Finance 98

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Data Pine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. The data warehouse. 1) The raw data.

Business Intelligence 108

Business Intelligence Business Intelligence Procurement Data Warehouse 108

Domo

APRIL 10, 2017

At Retail Week Live and Gartner Data & Analytics Conference 2017, both of which were held in the same building near the O2 Arena in London, we spoke with attendees about how Domo can solve their business problems. Traditional BI focuses on the central data warehouse, which includes their primary business data.

Retail 52

Retail Supply Chain Real-time Data Data Warehouse 52

Data Pine

JULY 1, 2020

Retail: Ad hoc data analysis proves particularly effective in loss prevention in the retail sector. In retail, it’s important to regularly track the sales volumes in order to optimize the overall performance of the online shop or physical stores.

Retail 104

Retail Healthcare Visualization Business Intelligence 104

The BAWorld

SEPTEMBER 18, 2024

Load : The formatted data is then transferred into a data warehouse or another data storage system. ELT (Extract, Load, Transform) This method proves to be efficient when both your data source and target reside within the same ecosystem. Extract: Data is pulled from its source.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Data Pine

SEPTEMBER 27, 2022

With a MySQL dashboard builder , for example, you can connect all the data with a few clicks. A host of notable brands and retailers with colossal inventories and multiple site pages use SQL to enhance their site’s structure functionality and MySQL reporting processes. It is a must-read for understanding data warehouse design.

IBM cost 117

IBM cost Data Warehouse Business Intelligence Business Intelligence 117

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

Agile 52

Agile Data Warehouse Data Quality Government 52

Actian

OCTOBER 24, 2019

When architecting your data warehouse solution, separating compute and data storage is extremely important for both operational sustainability and economic efficiency. Consider the example of black Friday in retail. Learn more about Actian Avalanche – Cloud Data Warehouse at www.actian.com/avalanche.

Cloud Computing 40

Cloud Computing Data Analytics Data Analytics Data Warehouse 40

Domo

SEPTEMBER 4, 2024

I wouldn’t even call it business intelligence anymore—it’s about growing data and analytics capabilities throughout the business. Before, we didn’t have a BI tool, a data warehouse, or a data lake—nothing. So, we started our journey in 2022, doing extensive research in all the data tools.

Retail 52

Retail Supply Chain Finance Master Data Management 52

Astera

MAY 30, 2023

They are responsible for collecting, transforming, and moving data from various sources to a central location for analysis and decision-making. Data pipelines can process data from different types of sources, including databases, files, and applications, and then store them in a central repository such as a data warehouse or a data lake.

Data Warehouse 52

Data Warehouse Data Management Retail Logistics 52

Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

Actian

OCTOBER 21, 2019

Azure is growing significantly as a platform in the enterprise space and becoming the de-facto choice for retail analytics. This is particularly appealing to those customers who have large amounts of data which is growing quickly but may not need compute to scale at the same pace.

Vision 40

Vision Data Warehouse Retail Data Discovery 40

Astera

NOVEMBER 30, 2023

With its foundation rooted in scalable hub-and-spoke architecture, Data Vault 1.0 provided a framework for traceable, auditable, and flexible data management in complex business environments. Building upon the strengths of its predecessor, Data Vault 2.0 Data Vault 2.0: can greatly simplify these processes.

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 52

Astera

SEPTEMBER 28, 2023

Reverse ETL is a relatively new concept in the field of data engineering and analytics. It’s a data integration process that involves moving data from a data warehouse, data lake, or other analytical storage systems back into operational systems, applications, or databases that are used for day-to-day business operations.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

Enforces data quality standards through transformations and cleansing as part of the integration process. Use Cases Use cases include data lakes and data warehouses for storage and initial processing. Use cases include creating data warehouses, data marts, and consolidated data views for analytics and reporting.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

Enforces data quality standards through transformations and cleansing as part of the integration process. Use Cases Use cases include data lakes and data warehouses for storage and initial processing. Use cases include creating data warehouses, data marts, and consolidated data views for analytics and reporting.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Domo

APRIL 12, 2021

Company X is a large regional retail chain centered in the Southeast. It recently closed a deal to buy Company Y, a similar retail chain with operations in the Midwest. Both companies have mature analytics environments with separate and different systems of record, databases, ETL tools, data warehouses, and BI tools.

Retail 52

Retail Data Warehouse Business Intelligence Business Intelligence 52

Astera

JUNE 14, 2023

Retail Point-of-Sale Systems: These systems enable retailers to process sales transactions, manage inventory, and track customer purchases. Differences between OLTP and OLAP The main differences between OLTP and OLAP lie in their purpose, data structure, and workload.

Supply Chain 40

Supply Chain Data Warehouse Financial Analysis Real-time Data 40

Data Pine

JANUARY 24, 2021

You are a retail company and want to know what you sell, where, and when – remember the specific questions for analyzing data? ETL data warehouse*. You just need to pick the right ones first and have them in agreement company-wide (or at least within your department). Let’s see this through a straightforward example.

Data Visualization 126

Data Visualization Data Analytics Data Analytics Data Quality 126

Astera

JANUARY 24, 2024

Modern data management relies heavily on ETL (extract, transform, load) procedures to help collect, process, and deliver data into an organization’s data warehouse. However, ETL is not the only technology that helps an enterprise leverage its data. It provides multiple security measures for data protection.

Data Warehouse 52

Data Warehouse Data Quality Data Management Data Security 52

Astera

DECEMBER 7, 2023

ETL refers to a process used in data integration and warehousing. It gathers data from various sources, transforms it into a consistent format, and then loads it into a target database, data warehouse , or data lake. Extract: Gather data from various sources like databases, files, or web services.

Supply Chain 52

Supply Chain E-Commerce Data Warehouse Real-time Data 52

Astera

MAY 31, 2024

Data integration combines data from many sources into a unified view. It involves data cleaning, transformation, and loading to convert the raw data into a proper state. The integrated data is then stored in a Data Warehouse or a Data Lake. Data warehouses and data lakes play a key role here.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Astera

JULY 13, 2023

This process includes moving data from its original locations, transforming and cleaning it as needed, and storing it in a central repository. Data integration can be challenging because data can come from a variety of sources, such as different databases, spreadsheets, and data warehouses.

Data Warehouse 40

Data Warehouse Data Quality Data Governance Master Data Management 40

Sisense

APRIL 2, 2020

“We crunch enormous Accounts Payable data files, and thousands of rebate agreements, and invoices,” Profectus’ Chief Technology Officer, Mark Webster told attendees. “In In the retail sector, for one of our biggest customers, we have 4TB of data that we crunch through every few months.

Vision 59

Vision Embedded Analytics Customer Experience Customer Experience 59

Astera

DECEMBER 7, 2023

ETL refers to a process used in data warehousing and integration. It gathers data from various sources, transforms it into a consistent format, and then loads it into a target database, data warehouse, or data lake. Extract: Gather data from various sources like databases, files, or web services.

Supply Chain 52

Supply Chain E-Commerce Real-time Data Data Warehouse 52

Actian

APRIL 17, 2019

During the past few years, there has been a strong shift in preferences from brick-and-mortar retail to online (Web) and mobile (app) purchasing. The challenge for these systems is processing market basket data in real-time. Actian Avalanche Cloud Data Warehouse can help. Market basket analysis in the digital age.

Data Warehouse 40

Data Warehouse Retail User Experience Data Analytics 40

Actian

JULY 16, 2019

Applications for IoT have included such diverse scenarios as monitoring manufacturing quality, optimizing power consumption in company facilities and tracking the flow of customers through retail stores. With many IoT devices, saving a couple of minutes of admin time on each device can add-up quickly.

Digital Transformation 40

Digital Transformation Data Warehouse Monitoring Real-time Data 40

Astera

SEPTEMBER 20, 2024

his setup allows users to access and manage their data remotely, using a range of tools and applications provided by the cloud service. Cloud databases come in various forms, including relational databases, NoSQL databases, and data warehouses. Common in-memory database systems include Redis and Memcached.

Data Warehouse 40

Data Warehouse Cloud Computing E-Commerce Documentation 40

Astera

MAY 13, 2024

It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. Some of these features include reporting tools, dashboards, and data modeling.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

AUGUST 3, 2023

The healthcare industry has HIPAA, while the retail industry has EDI standards such as AS2, AS3, and AS4. Astera EDI Connect seamlessly integrates with ETL (Extract, Transform, Load) functionality, enabling businesses to process received EDI data and maximize its value.

Healthcare 52

Healthcare Data Warehouse Retail Data Security 52

Astera

JUNE 14, 2023

It supports different data formats and offers features like data profiling, cleansing, mapping, and transformation to ensure high-quality data. DWBuilder : It simplifies the process of building and maintaining data warehouses. This allows it to adapt to changing business needs.

Procurement 40

Procurement Data Security Monitoring Retail 40

Astera

JUNE 13, 2023

Stream processing platforms handle the continuous flow of data, enabling real-time insights. Data Storage Once processed, data needs to be stored in appropriate repositories for further usage, such as data warehouses, data marts, operational databases, or cloud-based storage solutions.

E-Commerce 52

E-Commerce Data Quality Real-time Data Data Warehouse 52

Data Pine

MARCH 31, 2022

Problem-solving : BI isn’t just about analyzing data; it’s also about creating business strategies and solving real-world business problems with that data. For example, you could be the one to extract actionable insights from specific retail KPIs that need to be visualized and presented during a meeting.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

Astera

MAY 30, 2024

It relies on historical data and machine learning techniques to identify the likelihood of future outcomes. Example : Using predictive analytics, a retailer could predict future sales trends based on seasonal buying patterns and current market dynamics. Prescriptive Analytics: How to Make It Happen?

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Astera

NOVEMBER 27, 2023

Relationship Discovery: This process identifies the relationships and dependencies between different data elements. For example, in a customer database, content discovery reveals that the “Phone Number” column contains numerous missing values, highlighting incomplete contact information for certain customers.

Data Mining 52

Data Mining Data Quality Business Intelligence Business Intelligence 52

Business Analysis Knowledge Share

OCTOBER 27, 2023

This may involve data from internal systems, external sources, or third-party data providers. The data collected should be integrated into a centralized repository, often referred to as a data warehouse or data lake. Data integration ensures that all necessary information is readily available for analysis.

Business Intelligence 52

Business Intelligence Business Intelligence Supply Chain Data Governance 52