FineReport

SEPTEMBER 3, 2020

For most companies, using Excel to create reports is the most common reporting solution. However, with the growing amount of data from many sources, the pain points of using Excel are more and more apparent. For example, data collection is time-consuming, and the data from scattered business systems can not be integrated.

Reporting 95

Reporting Dashboards Visualization Data Warehouse 95

Laminar Security

APRIL 18, 2023

Laminar’s recent announcement of new features for its cloud-native Data Security Posture Management (DSPM) platform is a step towards meeting this challenge head-on. Laminar has become the first cloud-native DSPM solution to meet stringent and demanding enterprise requirements.

Enterprise 52

Enterprise Management Dashboards Snapshot 52

FineReport

FEBRUARY 12, 2020

The design of reports can be considered from two aspects: layout and system. You may have seen many articles emphasize how to improve the layout of the report. Today, let’s learn the report designing from the perspective of the report system. The Basics of Report Designing . The Basics of Report Designing .

Reporting 98

Reporting Metrics ROI KPI 98

AWS Big Data

MARCH 29, 2024

Grafana provides powerful customizable dashboards to view pipeline health. 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.

Metrics 108

Metrics Visualization Dashboards Interactive 108

Cloudera

OCTOBER 4, 2023

Ability to handle complex analytic queries — especially when we’re using real-time analytics to augment existing business dashboards and reports with large, complex, long-running business intelligence queries typical for those use cases, and not having the real-time dimension slow these down in any way. Kudu has this covered.

Data Warehouse 84

Data Warehouse Experimentation Cost-Benefit Dashboards 84

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 97

Management Data Warehouse Metrics Dashboards 97

CIO Business Intelligence

OCTOBER 17, 2023

NetSuite, an Oracle subsidiary, is a SaaS -based ERP provider offering a suite of applications that work together, reside on a common database, and are designed to automate core enterprise business processes. The company has added a new set of capabilities under the umbrella of NetSuite Enterprise Performance Management (EPM).

IT 131

IT Finance Sales Enterprise 131

CIO Business Intelligence

NOVEMBER 14, 2022

The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more. ERP dashboards. Data-driven DSS. Dashboards and other user interfaces that allow users to interact with and view results.

Data mining 144

Data mining Data-driven Statistics OLAP 144

FineReport

MARCH 21, 2020

Do you have the same problem with daily, weekly, or monthly reports? I summarized the problems typical with many daily, weekly, and monthly reports I have these years. . The process of data collection is time-consuming. Usually, the data is stored in Excel. Many report styles in the company are the same.

Reporting 91

Reporting Data Warehouse Manufacturing Enterprise 91

FineReport

DECEMBER 25, 2019

Reports are the basic business requirements of an enterprise. It can help enterprises make better use of data if different data can be presented by appropriate reports. Top 10 Types of Report. Detail Report. Top 10 Types of Report. Detail Report. Group Report. Split Report.

Reporting 98

Reporting Metrics ROI KPI 98

Jet Global

APRIL 2, 2019

Artificial Intelligence is coming for the enterprise. Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. The road to AI supremacy in enterprise business starts with investment in an area most businesses might not think to look at first.

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

AWS Big Data

MAY 25, 2023

Many organizations today are using AWS Glue to build ETL pipelines that bring data from disparate sources and store the data in repositories like a data lake, database, or data warehouse for further consumption. The email is formatted via HTML output that provides tables for the aggregated job run data.

Reporting 70

Reporting Metrics Optimization Data Lake 70

Jet Global

AUGUST 14, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Flat files – Other systems supply data in the form of flat files of different formats.

Data Warehouse 108

Data Warehouse Testing Data Quality Reporting 108

DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data. DataOps Success Story.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

Cloudera

SEPTEMBER 17, 2018

However, as the data warehousing world shifts into a fast-paced, digital, and agile era, the demands to quickly generate reports and help guide data-driven decisions are constantly increasing. Consider the following: More data types to be queried, but increasingly the data resides in separate silos.

Data Warehouse 52

Data Warehouse Optimization Visualization Unstructured Data 52

IBM Big Data Hub

OCTOBER 16, 2023

In other words, instead of training numerous models on labeled, task-specific data, it’s now possible to pre-train one big model built on a transformer and then, with additional fine-tuning, reuse it as needed. They offer an enterprise-ready dataset with trusted data that’s undergone negative and positive curation.

Risk 76

Risk Modeling Management Metadata 76

datapine

MAY 21, 2019

These past BI issues may discourage them to adopt enterprise-wide BI software. The price of deploying BI is a primary concern among small and medium-sized enterprises (SMEs). In the past, expensive enterprise BI solutions required huge hardware resources. Ineffective dashboards can be easily updated to focus on business needs.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

FineReport

JULY 28, 2021

Definition: BI vs Data Science vs Data Analytics. Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

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. When running properly, it provides timely and trustworthy information.

Metrics 98

Metrics Data Lake Cost-Benefit Dashboards 98

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Octopai

FEBRUARY 12, 2020

A data dictionary is a tool that organizes and describes different variables indicated by metadata associated with a dataset. A business glossary, sometimes referred to as a data glossary , is a broader tool. It defines terminology used by multiple departments across an enterprise. Get Good Stuff by Having a Data Dictionary.

Metadata 54

Metadata Enterprise Management Data Warehouse 54

Jet Global

OCTOBER 2, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Digital Transformation 105

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 105

AWS Big Data

MAY 10, 2023

A write-back is the ability to update a data mart, data warehouse, or any other database backend from within BI dashboards and analyze the updated data in near-real time within the dashboard itself. AnyCompany wants to build a new dashboard with quote history data for analysis and business insights.

Dashboards 76

Dashboards Data Warehouse Visualization Data Processing 76

CIO Business Intelligence

SEPTEMBER 14, 2023

They’re often responsible for building algorithms for accessing raw data, too, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics. What Are Data Entities?

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. The SQL query language used to extract data for reporting could also potentially be used to insert, update, or delete records from the database.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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

FineReport

JULY 23, 2020

In today’s fast-paced technological environment, everyone’s focus is often on the concept such as “data middle-platform”, “data warehouse”, and so on. Many people often overlook the basis of company operations: reports. For IT engineers, the main difficulties in making reports are. Sales Report.

IT 98

IT Reporting Visualization Data Warehouse 98

DataRobot Blog

FEBRUARY 28, 2023

According to Flexera 1 , 92% of enterprises have a multi-cloud strategy, while 80% have a hybrid cloud strategy. Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI.

Data Processing 72

Data Processing Experimentation Machine Learning Modeling 72

FineReport

NOVEMBER 17, 2021

However, Tableau may not work for each enterprise in the world. Report and Dashboard. The component settings of the dashboard are very powerful. The component settings of the dashboard are very powerful. You can make changes to data and graphs or even data points directly on the chart. FineReport.

KPI 52

KPI Dashboards Metadata Data Warehouse 52

Alation

MARCH 29, 2022

In the 1970s, data was confined to mainframes and primitive databases. Reports required a formal request of the few who could access that data. The 1980s ushered in the antithesis of this version of computing — personal computing and distributed database management — but also introduced duplicated data and enterprise data silos.

Business Intelligence 96

Business Intelligence Reporting Data mining Data-driven 96

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

Jet Global

APRIL 20, 2020

A new paradigm in reporting and analysis is emerging. There was always a delay between the events being recorded in financial systems (for example, the purchase of a product or service) and the ability to put that information in context and draw useful conclusions from it (for example, a weekly sales report).

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

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. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conceivable business function.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73