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 113

Metrics Visualization Dashboards Interactive 113

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 72

Reporting Metrics Optimization Data Lake 72

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Cloudera Data Warehouse).

Metrics 83

Metrics Slice and Dice Data Warehouse Dashboards 83

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. 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.

Data mining 144

Data mining Data-driven Statistics OLAP 144

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. Optimization.

Data Warehouse 52

Data Warehouse Optimization Visualization Unstructured Data 52

Sisense

JULY 7, 2020

Sisense News is your home for corporate announcements, new Sisense features, product innovation, and everything we roll out to empower our users to get the most out of their data. Today’s organizations are more data-driven than ever. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses.

Slice and Dice 92

Slice and Dice Data Warehouse Analytics Dashboards 92

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 102

Management Data Warehouse Metrics Dashboards 102

Smart Data Collective

OCTOBER 27, 2021

The data is ever-increasing, and getting the deepest analytics about their business activities requires technical tools, analysts, and data scientists to explore and gain insight from large data sets. Interactive analytics applications make it easy to get and build reports from large unstructured data sets fast and at scale.

Interactive 112

Interactive Unstructured Data Analytics Data Warehouse 112

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. From 2019 to now, Wang reports the amount of data the company holds has grown by a factor of 20.

Data Warehouse 119

Data Warehouse Cost-Benefit Sales Data-driven 119

datapine

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. These businesses include eBay, Autotrader, and Amazon.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

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

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. The end benefit for you is more effective and optimized AWS Glue for Apache Spark workloads.

Metrics 103

Metrics Data Lake Cost-Benefit Dashboards 103

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. In addition to increasing the price of deployment, setting up these data warehouses and processors also impacted expensive IT labor resources.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

datapine

NOVEMBER 19, 2019

Social BI indicates the process of gathering, analyzing, publishing, and sharing data, reports, and information. This is done using interactive Business Intelligence and Analytics dashboards along with intuitive tools to improve data clarity. They can also optimize their time if they don’t have to reinvent a report.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

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

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 76

Risk Modeling Management Metadata 76

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Scientist.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

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

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

CDW Research Hub

APRIL 20, 2020

Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications. Connecting ThoughtSpot and Snowflake is a simple 3-step process.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

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 74

Analytics Data Warehouse Data Lake Metadata 74

datapine

SEPTEMBER 29, 2022

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. But first, let’s define what data quality actually is. 4 – Data Reporting.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

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

AWS Big Data

JUNE 28, 2023

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. However, to realize this growth, managing and preparing the data for analysis has to get easier.

Analytics 72

Analytics Data Warehouse Data Lake Data-driven 72

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

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

Sisense

JUNE 8, 2020

Datasets are on the rise and most of that data is on the cloud. The recent rise of cloud data warehouses like Snowflake means businesses can better leverage all their data using Sisense seamlessly with products like the Snowflake Cloud Data Platform to strengthen their businesses.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

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

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. New data is shared with users by updating reporting schema several times a day.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

Jet Global

APRIL 2, 2019

But business intelligence software , built to give businesses the opportunity to collect, unify, sort, tag, analyze, and report on the vast amounts of data at their disposal, must be a focus for businesses hoping to gain an AI advantage down the road. It All Starts with Data. Which problems do disparate data points speak to?

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

Jet Global

JANUARY 15, 2020

It’s data analysis instead of just collection and reporting. It’s insight that creates and enables value, not just reporting on business performance. Financial intelligence starts by recognizing something fundamental about financial data. Reporting structures don’t roll up into nice neat hierarchies, and they change.

IT 59

IT Finance Reporting Data-driven 59

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. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Sisense

APRIL 2, 2020

Tools of the Trade is your destination for data and analytics skill building: From dashboards and reports to embedding analytics and building custom analytic apps to SQL secrets and data deep-dives, whatever you need to know to be better at your job, you can find it here. SQL Cheat Sheet & Query Syntax.

Data Warehouse 83

Data Warehouse Big Data Testing Software 83

Jet Global

AUGUST 14, 2019

Which problems do disparate data points speak to? And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. So how is the data extracted?

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

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