Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. Get these wrong and chances are your enterprise processes and systems will suffer.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

BizAcuity

MAY 16, 2022

As a data analytics company, we have been observing a trend among certain large enterprises who are looking for real-time data streaming for analytics. So, make sure you have a data strategy in place. Data Integration. Data mining. Visual Analytics and Data Visualization.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. She has a long history of working in the enterprise software and data services spaces.

Data Quality 94

Data Quality Statistics Data Lake Visualization 94

FineReport

MAY 31, 2023

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). These indicators indirectly shed light on the enterprise’s operational conditions.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Andrew White

OCTOBER 22, 2021

Monetization/Link data to outcome (value pyramid) business value of data/business impact 20. Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13. Lakehouse (data warehouse and data lake working together) 8.

IT 52

IT Data Lake Strategy Data Science 52

Jet Global

OCTOBER 7, 2020

It uses its own data mart, which cannot be customized in any way. Power BI is an analytical tool for data visualization and discovery. When working with D365 F&SCM data, it typically requires specialized programming skills to develop reports or to make changes to existing reports. Enterprise Business Intelligence.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

CIO Business Intelligence

JUNE 7, 2022

But the success of their AI initiatives depends on more than just data and technology — it’s also about having the right people on board. An effective enterprise AI team is a diverse group that encompasses far more than a handful of data scientists and engineers. Data scientist. Data steward.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

erwin

MAY 2, 2022

I was pricing a data warehousing project with just 4 TB of data – small by today’s standards. I chose “OnDemand” for up to 64 virtual CPUs and 448 GB of memory, since this data warehouse wanted to leverage in-memory processing. So that’s $136,000 per year just to run this one data warehouse in the cloud.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

Birst BI

OCTOBER 30, 2018

Instead of transacting business with only a paper record, enterprise applications recorded transactions in a computer database. Because the data describing each transaction was in a database, this made it easy to retrieve and summarize multiple transactions together. Add the predictive logic to the data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

FineReport

MAY 9, 2020

The data layer of FineReport is responsible for data management, including data collection, ETL, building a data warehouse, etc. It supports multiple data sources and data integration. . Top 20 Best Data Visualization Software in 2020: Free and Commercial.

Reporting 52

Reporting Sales Data Warehouse Software 52

Jet Global

MARCH 25, 2020

According to a recent survey by the Hackett Group, 90 percent of finance respondents rated improving enterprise data and analytics capabilities as highly important or even critical. Not having direct access to the data you need hinders your ability to deliver on-demand reporting. View Whitepaper Now.

Reporting 45

Reporting Finance Sales Visualization 45

AWS Big Data

FEBRUARY 13, 2024

AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue. With Grafana, you can create, explore, and share visually rich, data-driven dashboards. Graph lines are visualized per job.

Metrics 99

Metrics Dashboards Visualization Key Performance Indicator 99

CIO Business Intelligence

OCTOBER 7, 2022

BI analysts, with an average salary of $71,493 according to PayScale , provide application analysis and data modeling design for centralized data warehouses and extract data from databases and data warehouses for reporting, among other tasks. BI encompasses numerous roles.

Business Intelligence 145

Business Intelligence Data Warehouse Visualization Dashboards 145

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. One of the most common use cases for data preparation on Amazon Redshift is to ingest and transform data from different data stores into an Amazon Redshift data warehouse.

Visualization 77

Visualization Data Warehouse Big Data Data Lake 77

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 92

Data Analytics Analytics Data Warehouse Data Lake 92

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 91

Data Warehouse Visualization Data-driven Data Architecture 91

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 102

Data Warehouse Data Lake Analytics Machine Learning 102

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. Data ingestion/integration services. Reverse ETL tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

FineReport

JULY 16, 2021

Among these problems, one is that the third party on market data analysis platform or enterprises’ own platforms have been unable to meet the needs of business development. With the advancement of information construction, enterprises have accumulated massive data base. Data Warehouse. Data Analysis.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

AWS Big Data

NOVEMBER 29, 2023

With Amazon Bedrock , you can privately customize FMs for your specific use case using a small set of your own labeled data through a visual interface without writing any code. Building a strong data foundation To produce the high-quality data that you need to build or customize FMs for generative AI, you need a strong data foundation.

Data Warehouse 111

Data Warehouse Data Lake Data Integration Dashboards 111

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

Data Warehouse 94

Data Warehouse Data Integration Marketing Software 94

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process.

Testing 300

Testing Machine Learning Consulting Data Quality 300

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Users interested in visual exploration can do so using AWS Glue DataBrew.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 130

Data Warehouse Data Lake Visualization Big Data 130

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). for DG adoption in the enterprise. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 89

Management Metadata Data Architecture Data Lake 89

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. SQL Server Integration Services (SSIS): You know it; your father used it.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

Data Virtualization

APRIL 30, 2020

We are in the midst of a significant transformation in each and every sphere of business. We are witnessing an Industrial 4.0 revolution across the industrial sectors. The way products are getting manufactured is being transformed with automation, robotics, and.

Manufacturing 52

Manufacturing Digital Transformation Optimization Data Warehouse 52

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

Data Warehouse 91

Data Warehouse Optimization Dashboards Interactive 91

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

Jedox

MARCH 11, 2021

They are contrary to the approach of a data warehouse. The large, round towers are visually striking and normally used to store grain and other materials, often in rural areas. Most systems for tools such as CRM and ERP offer functions that allow automated data exports. So that’s it? No, not yet.

Sales 80

Sales Optimization Digital Transformation Data Warehouse 80

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Good Visualization Options.

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

IBM Big Data Hub

OCTOBER 12, 2023

Ensuring compliance with governmental regulatory requirements as well as internal policies An AI model must be fully understood from every angle, inside and out—from what enterprise data is used and when , to how the model arrived at a certain output. Learn more about IBM watsonx 1.

Cost-Benefit 84

Cost-Benefit Metadata Data Governance Modeling 84

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Finally, data integrity is of paramount importance. Every event in the data source can be relevant, and our customers don’t tolerate data loss, poor data quality, or discrepancies between the source and Tricentis Analytics.

Software 52

Software Data Lake Testing Cost-Benefit 52