AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 81

Enterprise Data Warehouse Snapshot Cost-Benefit 81

datapine

MARCH 31, 2022

To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools. Front-end analytical and business intelligence skills are geared more towards presenting and communicating data to others. b) If You’re Already In The Workforce.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

Data Warehouse 80

Data Warehouse Analytics Metadata Dashboards 80

FineReport

MAY 31, 2023

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). It is generally advisable to maintain a quick ratio above 100%.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. to create forecast tables and visualize the data. and Karra Taniskidou, E.

Forecasting 80

Forecasting Data Warehouse Machine Learning Modeling 80

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Amazon SageMaker Model Monitor provides a proactive detection of deviations in model data quality drift and model quality metrics drift.

Data Governance 94

Data Governance Unstructured Data Metadata Data Lake 94

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. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

FineReport

FEBRUARY 12, 2020

One of the report tasks is to “paint a picture” of a business topic with multiple associated metrics with a hierarchy. e.g., If you focus on user growth, you can sort through the user categories, the key metrics of each AARRR phases, the results of products or operational activities related to user growth, ROIs, and so on.

Reporting 98

Reporting Metrics ROI KPI 98

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. For an up-to-date list, refer to Data Quality Definition Language (DQDL).

Data Quality 92

Data Quality Statistics Data Lake Visualization 92

AWS Big Data

FEBRUARY 13, 2024

AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue. This post, walks through how to integrate AWS Glue job observability metrics with Grafana using Amazon Managed Grafana. Choose Administration.

Metrics 96

Metrics Dashboards Visualization Key Performance Indicator 96

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

FineReport

DECEMBER 25, 2019

One of the report tasks is to “paint a picture” of a business topic with multiple associated metrics with a hierarchy. e.g., If you focus on user growth, you can sort through the user categories, the key metrics of each AARRR phases, the results of products or operational activities related to user growth, ROIs, and so on.

Reporting 98

Reporting Metrics ROI KPI 98

CIO Business Intelligence

NOVEMBER 22, 2022

External data sharing gets strategic Data sharing between business partners is becoming far easier and much more cooperative, observes Mike Bechtel, chief futurist at business advisory firm Deloitte Consulting.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

AWS Big Data

JANUARY 8, 2024

The destination can be an event-driven application for real-time dashboards, automatic decisions based on processed streaming data, real-time altering, and more. With Kinesis Data Streams, customers can continuously capture terabytes of time series data from thousands of sources for cleaning, enrichment, storage, analysis, and visualization.

Analytics 110

Analytics IoT Data-driven Snapshot 110

datapine

MAY 21, 2019

In addition to increasing the price of deployment, setting up these data warehouses and processors also impacted expensive IT labor resources. These tools allow for a wide range of users to easily connect to, interact with, visualize and communicate their data. 7) Dealing with the impact of poor data quality.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

AWS Big Data

MARCH 25, 2024

Stream processing, however, can enable the chatbot to access real-time data and adapt to changes in availability and price, providing the best guidance to the customer and enhancing the customer experience. When the model finds an anomaly or abnormal metric value, it should immediately produce an alert and notify the operator.

Data Lake 89

Data Lake Unstructured Data Management Modeling 89

CIO Business Intelligence

JUNE 7, 2022

A data scientist is a mix of a product analyst and a business analyst with a pinch of machine learning knowledge, says Mark Eltsefon, data scientist at TikTok. AI strategists can also help organizations obtain the data they need to fuel AI effectively.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

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.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

DataKitchen

JANUARY 3, 2022

Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units. Business analysts sometimes perform data science, but usually, they integrate and visualize data and create reports and dashboards from data supplied by other groups.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

Jet Global

OCTOBER 7, 2020

It uses its own data mart, which cannot be customized in any way. Power BI is an analytical tool for data visualization and discovery. When working with D365 F&SCM data, it typically requires specialized programming skills to develop reports or to make changes to existing reports. Enterprise Business Intelligence.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

JUNE 6, 2023

It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines. Data quality at rest focuses on validating the data stored in data lakes, databases, or data warehouses. It ensures that the data meets specific quality standards before it is consumed.

Data Quality 66

Data Quality Data Lake Visualization Data-driven 66

Smarten

DECEMBER 3, 2023

You cannot present a comprehensive solution and set metrics for success if you don’t understand the issues. Perhaps you want to shift from a data warehouse to cloud storage. What problems will it solve? What opportunities does it present? Involving Stakeholders, Customers, Users, IT, etc. Do not work in a vacuum!

Analytics 40

Analytics Data Warehouse Metrics Interactive 40

Smart Data Collective

JULY 22, 2019

For this reason, businesses of every scale have tons of metrics they monitor, organize and analyze. In many cases, data processing includes manual data entrance , painful hours of calculations and stats drafting. Sisense processes data a lot faster compared to many other similar BI tools.

Business Intelligence 80

Business Intelligence Cost-Benefit Dashboards Visualization 80

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

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

DataKitchen

OCTOBER 5, 2021

Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires. Their product is the data.

Testing 157

Testing Dashboards Measurement Experimentation 157

Birst BI

OCTOBER 30, 2018

Descriptive analytics techniques are often used to summarize important business metrics such as account balance growth, average claim amount and year-over-year trade volumes. Identify the metric you want to influence through predictive analytics. What business metric determines the success of your organization?

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

AWS Big Data

MARCH 2, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data. Grafana provides a predefined dashboard to visualize database privileges.

Visualization 75

Visualization Dashboards Data Warehouse Metrics 75

Smarten

NOVEMBER 22, 2017

Fortunately, today’s new self-serve business intelligence solutions allow for ease-of-use, bringing together these varied techniques in a simple interface with tools that allow business users to utilize advanced analytics without the skill or knowledge of a data scientist, analyst or IT team member.

Analytics 40

Analytics IT Business Intelligence Visualization 40

Jet Global

JANUARY 15, 2020

As you’re building your financial intelligence, keep these questions top of mind: Is your company leveraging the right data in decision making? How do you acquire data to fill in metrics, KPIs, or data visuals? What would easier data access for decision making look like? Roadblocks to Financial Intelligence.

IT 59

IT Finance Reporting Data-driven 59

Jet Global

OCTOBER 2, 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 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Occam's Razor

SEPTEMBER 9, 2013

One of the key things we are going to learn today is to align our metrics and dimensions optimally to ensure we report good, clean, sensible data. The above graphic is from post, Excellent Analytics Tip #23: Align Hits, Sessions, Metrics, Dimensions! Your effort will make this post 100x more valuable. Four different people.

Analytics 145

Analytics Metrics Marketing Reporting 145

CIO Business Intelligence

OCTOBER 19, 2023

Power BI is Microsoft’s interactive data visualization and analytics tool for business intelligence (BI). With Power BI, you can pull data from almost any data source and create dashboards that track the metrics you care about the most. What-if parameters also create calculated measures you can reference elsewhere.

Slice and Dice 126

Slice and Dice Scorecard Metrics Visualization 126

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Jet Global

MARCH 25, 2020

Not having direct access to the data you need hinders your ability to deliver on-demand reporting. Do you need to provide visualizations to help other departments manage their costs and expenses? Do you need to validate master data in your reporting? non-financial) data in your financial reports?

Reporting 45

Reporting Finance Sales Visualization 45