IBM Big Data Hub

NOVEMBER 6, 2023

As such, enterprises that serve SMBs must provide solutions that lessen administrative burdens and deliver tangible value. By adopting these 4 best practices to invest in the right technology and leverage the most recent advances in generative AI , enterprises can unlock unique services for SMB customers.

Cost-Benefit 109

Cost-Benefit Enterprise ROI Data Warehouse 109

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. These DSS include systems that use accounting and financial models, representational models, and optimization models.

Data mining 144

Data mining Data-driven Statistics OLAP 144

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. Analyzing historical patterns allows you to optimize performance, identify issues proactively, and improve planning.

Metrics 108

Metrics Visualization Dashboards Interactive 108

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 95

Data Warehouse Data-driven Machine Learning B2B 95

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

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

Cloudera

SEPTEMBER 17, 2018

These trends and demands lead to stress for existing data warehouse solutions – scale, efficiency, security integrations, IT budgets, ease of access. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution. No need to be a 100% expert on your data. Optimization.

Data Warehouse 52

Data Warehouse Optimization Visualization Unstructured Data 52

CIO Business Intelligence

MARCH 28, 2022

After launching the Healthcare and Life Sciences Data Cloud Platform just a week ago, Snowflake has announced a Retail Data Cloud aimed at helping retail and consumer goods companies make the most of their data. The Retail Data Cloud will also include prebuilt data applications from various technology and consulting partners.

Consulting 125

Consulting Data Warehouse Machine Learning Dashboards 125

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

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

Armed with BI-based prowess, these organizations are a testament to the benefits of using online data analysis to enhance your organization’s processes and strategies. These past BI issues may discourage them to adopt enterprise-wide BI software. In the past, expensive enterprise BI solutions required huge hardware resources.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

AWS Big Data

NOVEMBER 20, 2023

The new metrics provide aggregate and fine-grained insights into the health and operations of your job runs and the data being processed. In addition to providing insightful dashboards, the metrics provide classification of errors, which helps with root cause analysis of performance bottlenecks and error diagnosis. Check it out!

Metrics 98

Metrics Data Lake Cost-Benefit Dashboards 98

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

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. Cold storage is optimized to store infrequently accessed or historical data.

Data Lake 116

Data Lake Analytics Dashboards Metrics 116

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

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

datapine

NOVEMBER 19, 2019

This can be done with the help of socializing ideas within an Enterprise Business Intelligence tool, be it with or without an Enterprise Social Network (ESN). Social BI indicates the process of gathering, analyzing, publishing, and sharing data, reports, and information. Summing Up.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

CIO Business Intelligence

JUNE 14, 2023

CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP. Individuals with the certificate understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL, and R.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

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. Our Value Proposition How does TopQuadrant fit into this picture?

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

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

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

AWS Big Data

JANUARY 8, 2024

In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices. All these architecture patterns are integrated with Amazon Kinesis Data Streams. The raw data can be streamed to Amazon S3 for archiving.

Analytics 115

Analytics IoT Data-driven Snapshot 115

DataKitchen

NOVEMBER 4, 2021

It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows. The DataKitchen Platform is a “ process hub” that masters and optimizes those processes. One data engineer called it the “last mile problem.” . It’s that simple. .

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. The more effectively a company uses data, the better it performs. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

datapine

SEPTEMBER 29, 2022

Paired to this, it can also: Improved decision-making process: From customer relationship management, to supply chain management , to enterprise resource planning, the benefits of effective DQM can have a ripple impact on an organization’s performance. A metric to evaluate timeliness is the data time-to-value.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jet Global

OCTOBER 7, 2020

For anyone that needs to develop custom reports and dashboards, it all begins with understanding data entities. What Are Data Entities? Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

APRIL 20, 2020

First, accounting moved into the digital age and made it possible for data to be processed and summarized more efficiently. Spreadsheets enabled finance professionals to access data faster and to crunch the numbers with much greater ease. Today’s technology takes this evolution a step further.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

Jet Global

JUNE 5, 2019

Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. So how does a leading-edge business find a way to marry their wealth of data with the opportunity to utilize it effectively via BI software? Start future proofing your business today.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

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

datapine

JANUARY 24, 2021

If nothing can be changed, there is no point of analyzing data. But if you find a development opportunity, and see that your business performance can be significantly improved, then a KPI dashboard software could be a smart investment to monitor your key performance indicators and provide a transparent overview of your company’s data.

IT 317

IT Statistics KPI Data-driven 317

Timo Elliott

OCTOBER 3, 2019

For example, Gerd Danner explained the digital core strategy of S/4HANA is key part of the journey, emphasizing that while the new platform gives you a lot more real-time analytic power, without any data duplication, you still need a data warehouse and analytics strategy over time and across different systems.

Data Warehouse 63

Data Warehouse Digital Transformation Machine Learning Strategy 63

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. jobs because this feature will help reduce cost and optimize your ETL jobs.

Reporting 70

Reporting Metrics Optimization Data Lake 70

Octopai

SEPTEMBER 10, 2020

It usually goes something like this: “Using state-of-the-art tools and techniques, leveraging your creativity and understanding of business operations and data structures to combine data from disparate sources to generate reports, dashboards, and other deliverables to provide actionable business insights to key stakeholders.

Business Intelligence 52

Business Intelligence Data Warehouse Dashboards Reporting 52

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 78

Data Lake Data Warehouse Sales Data-driven 78