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. Data orchestration tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 97

Dashboards Analytics Metadata Data Warehouse 97

Cloudera

JUNE 2, 2022

Use cases demand that data no longer be distributed to just a data warehouse or subset of data sources, but to a diverse set of hybrid services across cloud providers and on-prem. . Instead they built or purchased tools for data collection that are confined with a class of sources and destinations.

Enterprise 102

Enterprise Data Lake Data Collection Data-driven 102

erwin

FEBRUARY 28, 2019

Residents want the ability to pay their taxes online, report a pothole from their phone, and generally make it easier to interact with their local officials and services. When you have the ability to understand all of the information related to a piece of data, you have more confidence in how it is analyzed, used and protected.

Digital Transformation 106

Digital Transformation Data Governance Data-driven Data Warehouse 106

IBM Big Data Hub

JANUARY 10, 2023

This allows data that exists in cloud object storage to be easily combined with existing data warehouse data without data movement. The advantage to NPS clients is that they can store infrequently used data in a cost-effective manner without having to move that data into a physical data warehouse table.

Data Warehouse 52

Data Warehouse Cost-Benefit Statistics Data Processing 52

Ontotext

NOVEMBER 16, 2023

In a data mesh, domains are represented by a node, which can be an operational data store (ODS), a data warehouse, or a data lake tailored to the domain’s requirements. The owner also provides infrastructure and mechanisms to permit data producers and consumers to interact.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

CIO Business Intelligence

JULY 13, 2022

Use cases demand that data no longer be distributed to just a data warehouse or subset of data sources, but to a diverse set of hybrid services across cloud providers and on-prem. . Instead they built or purchased tools for data collection that are confined with a class of sources and destinations.

Enterprise 65

Enterprise Data Lake Data Collection Data-driven 65

Jet Global

AUGUST 14, 2019

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. Cognitive engagement applications can be used to automate interactions between people and systems, either externally (for customers), or internally (for employers).

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

IBM Big Data Hub

AUGUST 4, 2023

Architecture for data democratization Data democratization requires a move away from traditional “data at rest” architecture, which is meant for storing static data. Traditionally, data was seen as information to be put on reserve, only called upon during customer interactions or executing a program.

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62

datapine

FEBRUARY 22, 2022

This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? Businesses deal with massive amounts of data from their users that can be sensitive and needs to be protected. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

FineReport

FEBRUARY 28, 2020

Enterprise reporting is a process of extracting, processing, organizing, analyzing, and displaying data in the companies. It uses enterprise reporting tools to organize data into charts, tables, widgets, or other visualizations. Via the interactive analysis such as drill-down, the problems in business can be located. .

Reporting 96

Reporting Enterprise Visualization Business Intelligence 96

Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

Cost-Benefit 92

Cost-Benefit IoT Data Warehouse Manufacturing 92

Cloudera

JANUARY 11, 2018

Data science and advanced analytics deliver more value if organizations can deploy models and algorithms on detailed data brought together from many sources, not just on summaries or samples contained in a single data warehouse or data mart.” External social media data could also be valuable for analysis.”

Strategy 40

Strategy Data Warehouse Cost-Benefit Marketing 40

Jet Global

OCTOBER 2, 2019

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. Cognitive engagement applications can be used to automate interactions between people and systems, either externally (for customers), or internally (for employers).

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Cloudera

JANUARY 11, 2021

Interactive demo sessions and live Q&A are what we all need these days when working remotely from home is now a norm. NiFi is like the mailman who delivers the data to the mailbox or a different destination. NiFi is a great, consistent, and unique software to manage all your data ingestion. The most common protocol is HTTP.

Data Processing 61

Data Processing Interactive ROI Data Warehouse 61

Jet Global

OCTOBER 4, 2022

In addition to being time-consuming to create, the reports are often on pages and pages of spreadsheets, and there’s no good way to include nonfinancial data when you’re looking at a wall of numbers. Inability to see interactions between your financial and nonfinancial data makes it much harder to tell the story behind the numbers.

Visualization 52

Visualization Reporting Forecasting Dashboards 52

Jet Global

FEBRUARY 20, 2024

Exceed expectations with prompt deliveries and build trust with every interaction. Streamlined Operations : Automate tedious tasks like data collection and reporting. Faster Deliveries, Happy Customers : Track shipments in real-time, address issues proactively, and keep customers informed.

Operational Reporting 52

Operational Reporting Reporting Digital Transformation Optimization 52

Jet Global

AUGUST 9, 2023

Not just because they reduce your time spent creating reports, but also because they end your reliance on manual spreadsheets that require countless hours checking and double-checking thousands of lines of data for accuracy.

Finance 52

Finance Reporting Cost-Benefit Forecasting 52

Alation

AUGUST 26, 2021

Data intelligence first emerged to support search & discovery, largely in service of analyst productivity. For years, analysts in enterprises had struggled to find the data they needed to build reports. This problem was only exacerbated by explosive growth in data collection and volume. Data lineage features.

Metadata 64

Metadata Data Governance Dashboards Software 64

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Let’s just give our customers access to the data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Occam's Razor

MARCH 23, 2010

Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. A majority of web analytics data warehousing efforts fail. Why do you think introducing a completely different set of numbers is going to make your life easier? It will be humbling.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. You also had the launch of smartphones.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

FEBRUARY 4, 2019

These two points provide a different kind of risk management mechanism which is effective for science, specifically data science. Of course, some questions in business cannot be answered with historical data. Instead they require investment, tooling, and time for data collection. Or something.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66