AWS Big Data

JANUARY 8, 2024

It aims to provide a framework to create low-latency streaming applications on the AWS Cloud using Amazon Kinesis Data Streams and AWS purpose-built data analytics services. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 115

Analytics IoT Data-driven Snapshot 115

CIO Business Intelligence

SEPTEMBER 8, 2022

We’ve all experienced the pain of what continues to happen with the disconnect between customer usage metrics and gaps in supply chain data.” — Frank Cutitta ( @fcutitta ), CEO and Founder, HealthTech Decisions Lab “Operationally, think of logistics. Those decisions can have a direct impact on customers.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

IBM Big Data Hub

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. Having the right data strategy and data architecture is especially important for an organization that plans to use automation and AI for its data analytics.

Data Science 86

Data Science Data Analytics Prescriptive Analytics Analytics 86

Sisense

DECEMBER 23, 2019

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Once your data is prepared for analysis, the next question is: how else can AI help you? Apply that metric to any other business-critical function.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

Sisense

MARCH 6, 2019

The crowd who attends these events are made mostly of analytics leaders in Enterprises. It’s always fun and insightful to be able to talk to so many CDOs, CIOs, data and BI professionals within 2.5 I was very happy to see that the first key message – “Data Driven” – was subtitled with “Adopt an Experimental Mindset”.

Data Analytics 75

Data Analytics Analytics Experimentation Data-driven 75

Birst BI

OCTOBER 30, 2018

Remember when you began your career and the prospect of retirement was an event in the distant future? 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. Add the predictive logic to the data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Sisense

MAY 31, 2020

We’ve taken what we’ve learned from our customers and combined it with our own understanding of how the data and analytics world is evolving to drive innovations that unlock new possibilities and help our clients future-proof their products and services. Customer success isn’t a team sport – it’s a company value.

Marketing 98

Marketing Reporting Data Warehouse Predictive Analytics 98

AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

Data Warehouse 96

Data Warehouse Snapshot Testing Management 96

AWS Big Data

MARCH 26, 2024

The following figure shows some of the metrics derived from the study. A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

JUNE 28, 2023

Challenges Customers across industries today are looking to increase revenue and customer engagement by implementing near-real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more. The transactional data from this website is loaded into an Aurora MySQL 3.03.1 (or

Data Warehouse 86

Data Warehouse Analytics Metrics Dashboards 86

AWS Big Data

MARCH 21, 2024

Challenges Customers across industries today are looking to use data to their competitive advantage and increase revenue and customer engagement by implementing near real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more.

Data Warehouse 90

Data Warehouse Metrics Statistics Optimization 90

AWS Big Data

MARCH 20, 2024

To run analytics on your operational data, you might build a solution that is a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 125

Data Warehouse Business Driver Data Lake Data-driven 125

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

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. You can also create manual metrics to update yourself.

Slice and Dice 126

Slice and Dice Scorecard Metrics Visualization 126

CIO Business Intelligence

NOVEMBER 29, 2022

Increasing ROI for the business requires a strategic understanding of — and the ability to clearly identify — where and how organizations win with data. It’s the only way to drive a strategy to execute at a high level, with speed and scale, and spread that success to other parts of the organization. Data and cloud strategy must align.

Data Architecture 111

Data Architecture Data Integration IoT Strategy 111

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. For example, to create source-aligned datasets in the data lake for 3,000 operational tables, the company didn’t want to deploy 3,000 separate data processing jobs.

Data Lake 93

Data Lake Data Processing Metadata Snapshot 93

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 69

Modeling Sales Data Warehouse Snapshot 69

AWS Big Data

JANUARY 24, 2023

It contains references to data that is used as sources and targets in AWS Glue ETL (extract, transform, and load) jobs, and stores information about the location, schema, and runtime metrics of your data. The Data Catalog organizes this information in the form of metadata tables and databases.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

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

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Modeling 65

Occam's Razor

MARCH 10, 2015

Dimension Widening – hello sweet simple data from spreadsheets, data warehouses/CRM systems! Measurement Protocol – all your data are belong to us! It is the simple, but powerful, ability to send data into Google Analytics to enrich your understanding performance. They are: 1. Another scary name.

Strategy 151

Strategy Analytics Measurement Business Analysis 151

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

MARCH 9, 2023

Thousands of customers rely on Amazon Redshift to build data warehouses to accelerate time to insights with fast, simple, and secure analytics at scale and analyze data from terabytes to petabytes by running complex analytical queries. Data loading is one of the key aspects of maintaining a data warehouse.

Slice and Dice 82

Slice and Dice Data Warehouse Metrics Metadata 82

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Curious to learn how the data catalog can power your data strategy?

Metrics 52

Metrics Dashboards Sales Reporting 52

AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. Implementation strategy Based on these requirements, we changed strategies and started analyzing each issue to identify the solution. The data is partitioned on InputDataSetName, Year, Month, and Date.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Cloudera

OCTOBER 25, 2022

Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses. They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”. Network perimeter.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

Occam's Razor

JANUARY 30, 2012

When it comes to data analysis, you are usually more likely to see me share guidance on advanced segmentation or custom reports or advanced social metrics or controlled experiments or economic value or competitive intelligence or web analytics maturity or one of an infinite number of difficult, if hugely rewarding, things.

Analytics 145

Analytics Dashboards Metrics Key Performance Indicator 145

Smart Data Collective

FEBRUARY 20, 2022

Different DAM providers use different approaches to defining the key metrics that influence the cost of an off-the-shelf solution. On the one hand, the use of agents allows you to actively monitor and respond to events. By and large, you need to build an entire data protection strategy. There are different opinions.

Behavioral Analytics 117

Behavioral Analytics Risk Machine Learning Interactive 117

Sisense

MAY 11, 2021

In this article, we’ll dig into what data modeling is, provide some best practices for setting up your data model, and walk through a handy way of thinking about data modeling that you can use when building your own. Building the right data model is an important part of your data strategy. Discover why.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Birst BI

JUNE 18, 2018

Specialty’s Café and Bakery is a great example of a retailer that is using data to drive decisions related to product development and selection, inventories, staffing, and more to attract and keep customers. The third is to create a five-year strategy to obtain funding from our parent company FEMSA to grow our business.

Slice and Dice 76

Slice and Dice Machine Learning Sales Data-driven 76

Sisense

JANUARY 6, 2020

So, partnering with analysts to model Salesforce data will give sales teams more confidence to predict the revenue that teams are going to close at the end of any given period, and identify behaviors and strategies that will be most effective. Analysts can use SQL as a more powerful tool than Salesforce to model messy sales data.

Sales 91

Sales Forecasting Snapshot Management 91

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 85

Machine Learning Metrics Management Big Data 85

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Iceberg offers a Merge On Read strategy to enable fast writes.

Data Lake 116

Data Lake Metadata Optimization Statistics 116

Occam's Razor

FEBRUARY 7, 2011

But each keyword gets "credit" for other metrics. there are so many variables that drive demand (not just online but also offline and events etc.), because the data is so very not available. Parleo_ Q : what is most superficially tempting metric that is almost never worth worrying about? and finally 3.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Occam's Razor

JUNE 28, 2010

We have more web metrics and data than there are stars in the universe (slight exaggeration!). A large part of the reason is that a large part of our job seems to consist of glorified data puking, hoping someone will be impressed. After all there is so much data in those reports!! Yet we stink at informing decisions.

Metrics 111

Metrics Key Performance Indicator Data-driven Marketing 111