Ontotext

APRIL 10, 2024

Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience. Drowning in Data, Thirsting for Context We’ve heard the saying, “Data, data everywhere. Teams can’t access data to build their business use cases.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Jet Global

MARCH 25, 2020

While JD Edwards transactional data is required to run period close reports, analyze trends, and prepare forecasts for planning and budgeting, it comes with a lot of complexity. JD Edwards World has no less than 1600 tables of data to support just its business applications. 1 – What are all your reporting needs? .

Reporting 45

Reporting Finance Sales Visualization 45

AWS Big Data

MARCH 29, 2024

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. QuickSight lets you perform aggregate calculations on metrics for deeper analysis.

Metrics 101

Metrics Visualization Dashboards Interactive 101

AWS Big Data

JUNE 28, 2023

Data is at the center of every application, process, and business decision. When data is used to improve customer experiences and drive innovation, it can lead to business growth. times more likely than beginners to report at least 20% revenue growth. Firstly, it invariably requires data engineers to create custom code.

Analytics 66

Analytics Data Warehouse Data Lake Data-driven 66

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Metrics 92

Metrics Data Lake Cost-Benefit Dashboards 92

Smart Data Collective

JULY 20, 2021

Big data technology is incredibly important in modern business. One of the most important applications of big data is with building relationships with customers. These software tools rely on sophisticated big data algorithms and allow companies to boost their sales, business productivity and customer retention.

Sales 141

Sales Big Data Marketing Software 141

FineReport

MAY 31, 2023

In today’s dynamic business environment, gaining comprehensive visibility into financial data is crucial for making informed decisions. These reports include the cash flow statement, income statement, and balance sheet. Moreover, the software offers the convenient option of scheduling automated report delivery via email.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

BizAcuity

MAY 16, 2022

Fast food companies like Domino’s, McDonald’s and KFC collect massive amounts of data which includes customer data and other key business metrics for their own operations. Also, it is using customer data that they experiment and roll out new products every month. So, make sure you have a data strategy in place.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

Jet Global

MAY 1, 2020

Recently released is a report by Gartner about all the things that can go wrong in your BI implementation. In Gartner’s report, an analyst goes to great pains to say that there is “much more risk associated to non-technology issues than there is to deploying the infrastructure, tools, and apps.”. So, we feel validated. View Guide Now.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

IBM Big Data Hub

JANUARY 5, 2023

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

OCTOBER 20, 2023

Regarding the Azure Data Lake Storage Gen2 Connector, we highlight any major differences in this post. AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning, and application development. Learn more in README.

Data Lake 80

Data Lake Big Data Consulting Data Warehouse 80

Smarten

DECEMBER 7, 2017

In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to data warehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.

IT 40

IT Testing ROI Data Warehouse 40

erwin

MAY 2, 2022

I’m not proposing that business logic be held in the database, but it needs to be documented in the data model even if it will be implemented in application code. Data modeling helps you right-size cloud migrations for cost savings. I was pricing a data warehousing project with just 4 TB of data – small by today’s standards.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Alation

DECEMBER 15, 2022

Among all the internal celebrations, I wanted to take this moment to reflect on our journey so far and ask a thought-provoking question: who is the GOAT of data catalogs ? December 2012: Alation forms and goes to work creating the first enterprise data catalog. What Is a GOAT? How Do You Determine the GOAT for a Software Category?

Metadata 52

Metadata Data Governance Data Quality Marketing 52

FineReport

MAY 9, 2020

It divides the architecture into three tiers: data layer, application layer, and presentation layer. . By processing the business logic for the application, it builds a bridge between the presentation layer and the data layer to make communication faster between the presentation and data layer. Presentation Tier.

Reporting 52

Reporting Sales Data Warehouse Software 52

Octopai

JUNE 1, 2020

With the rapid rise of new data regulations across the globe, capable data mapping isn’t just a tool for companies to get a leg up on the competition – it is required for legal compliance. Let’s look at how these new requirements have changed the data landscape and how automated data mapping can give your company an advantage.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

Cloudera

FEBRUARY 11, 2019

The Magic Quadrant (MQ) is an established, widely-referenced series of research reports published by the analyst firm Gartner, Inc. The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. Cloudera’s 3 Key Takeaways.

Management 43

Management Metadata Analytics Machine Learning 43

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 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

erwin

JANUARY 11, 2019

But the attempts to standardize data across the entire enterprise haven’t produced the desired results. A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management.

Data Governance 40

Data Governance Risk Metadata Management 40

datapine

MAY 29, 2019

Business intelligence architecture is a term used to describe standards and policies for organizing data with the help of computer-based techniques and technologies that create business intelligence systems used for online data visualization , reporting, and analysis. One of the BI architecture components is data warehousing.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

Birst BI

OCTOBER 30, 2018

Because the data describing each transaction was in a database, this made it easy to retrieve and summarize multiple transactions together. This data retrieval and summarization capability gave rise to what we now know as the business intelligence industry. Add the predictive logic to the data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. Linked Data, subscriptions, purchased datasets, etc.).

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. They are opting for cloud data services more frequently.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Jet Global

JULY 26, 2022

Angles for Oracle simplifies the process of accessing data from Oracle ERPs for reporting and analytical insights; offering seamless integration with cloud data warehouse targets. Angles for Oracle has been an integral part of our operational reporting processes for 20 years. RALEIGH, N.C.—July

Data Integration 52

Data Integration Operational Reporting Data Warehouse Reporting 52

Jet Global

JULY 26, 2022

Angles for Oracle simplifies the process of accessing data from Oracle ERPs for reporting and analytical insights; offering seamless integration with cloud data warehouse targets. Angles for Oracle has been an integral part of our operational reporting processes for 20 years. RALEIGH, N.C.—July

Data Integration 52

Data Integration Operational Reporting Data Warehouse Reporting 52

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Place?

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

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.

Business Intelligence 145

Business Intelligence Data Warehouse Visualization Dashboards 145

Jet Global

MAY 27, 2022

Synapse services are powerful tools for bringing data together for analytics, machine learning, reporting needs, and more. Here, we discuss technology solutions that help you leverage the benefits of synapse services for mission-critical financial analysis and reporting in Microsoft Dynamics. Streamline Data with Atlas.

Data Lake 52

Data Lake IT Recreation/Entertainment Data Warehouse 52

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 97

Data Warehouse Data Lake Analytics Machine Learning 97

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

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

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 96

Data Warehouse Data Integration Marketing Software 96

datapine

NOVEMBER 11, 2021

a) Data Connectors Features. d) Reporting Features. For a few years now, Business Intelligence (BI) has helped companies to collect, analyze, monitor, and present their data in an efficient way to extract actionable insights that will ensure sustainable growth. Your Chance: Want to take your data analysis to the next level?

Business Intelligence 213

Business Intelligence Dashboards Interactive Visualization 213