Smart Data Collective

JUNE 30, 2022

Geoffrey Moore tweeted about this in 2012 when he said: “Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.”. Instagram marketing strategies will be far more effective if they utilize data analytics and artificial intelligence. Explaining How Instagram Stories Work.

Data-driven 109

Data-driven Marketing Strategy Big Data 109

AWS Big Data

MARCH 12, 2024

AWS Glue Data Quality is built on DeeQu , an open source tool developed and used at Amazon to calculate data quality metrics and verify data quality constraints and changes in the data distribution so you can focus on describing how data should look instead of implementing algorithms.

Data Quality 89

Data Quality Measurement Testing Visualization 89

AWS Big Data

FEBRUARY 28, 2024

OpenSearch Ingestion is a fully managed, serverless data collector that delivers real-time log, metric, and trace data to Amazon OpenSearch Service domains and Amazon OpenSearch Serverless collections. Terraform is an infrastructure as code (IaC) tool that helps you build, deploy, and manage cloud resources efficiently. touch main.tf

Metrics 65

Metrics Management Software Testing 65

Occam's Razor

JANUARY 2, 2013

In the coming year, based on current announcements , Google Analytics is set to go through an almost unprecedented amount of evolution. My favorite is Visitor Analytics, and visitor level segmentation that will be pervasive throughout the product. My postulation is that by this time next year the tool will be almost unrecognizable. [My

Strategy 159

Strategy Analytics Reporting Metrics 159

AWS Big Data

APRIL 3, 2024

Many organizations already use AWS Glue Data Quality to define and enforce data quality rules on their data, validate data against predefined rules , track data quality metrics, and monitor data quality over time using artificial intelligence (AI). The metrics are saved in Amazon S3 to have a persistent output. onData(df).useRepository(metricsRepository).addCheck(

Data Quality 89

Data Quality Visualization Metadata Metrics 89

Occam's Razor

MAY 14, 2012

A lot of digital analytics focuses on direct response (conversions, leads, etc.). But there is an additional valuable, and sexy, focus of our marketing we don't give enough analytical love: Branding! Bonus One: Read: Brand Measurement: Analytics & Metrics for Branding Campaigns ].

Measurement 128

Measurement Analytics Advertising Marketing 128

AWS Big Data

AUGUST 7, 2023

Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. The OBJECTIVE parameter specifies a metric to minimize or maximize the objective of a job. About the authors Tahir Aziz is an Analytics Solution Architect at AWS.

Forecasting 84

Forecasting Data Warehouse Machine Learning Modeling 84

datapine

JANUARY 6, 2022

In fact, a Digital Universe study found that the total data supply in 2012 was 2.8 Data interpretation refers to the process of using diverse analytical methods to review data and arrive at relevant conclusions. After its implementation in 2012, Intel saved over $3 million in manufacturing costs. trillion gigabytes!

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Ontotext

MAY 19, 2021

The resulting analytical platform can use these faculty impact metrics to inform research priorities and policy focus by understanding the institute’s impact on the wider academic community and identify what institutions are most likely to fund which research topics.

Publishing 72

Publishing Measurement Data-driven Metrics 72

datapine

MAY 14, 2019

It is also wise to clearly make a difference between data science and data analytics in a business context so that the exploration of the fields bring extra value for interested parties. 3) “Advanced R” by Hadley Wickham. click for book source**. Hands down one of the best books for data science.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

AWS Big Data

JUNE 28, 2023

In this post, we provide step-by-step guidance on how to get started with near-real time operational analytics using this feature. With Aurora zero-ETL integration with Amazon Redshift, you can bring together the transactional data of Aurora with the analytics capabilities of Amazon Redshift. or higher version) database.

Data Warehouse 85

Data Warehouse Analytics Metrics Dashboards 85

Sisense

JUNE 17, 2021

One of the biggest applications of data analytics in the marketing world is to define the demographics, behaviors, and interests of consumers, giving marketers a lens into who they’re targeting. Could data analytics have helped? Tip: Measure the metrics that matter. The marketer’s mantra could be: “ Know your audience.

Marketing 52

Marketing Interactive Metrics Advertising 52

AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, 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 most widely used cloud data warehouse.

Analytics 65

Analytics Data Warehouse Optimization Metrics 65

Alation

MARCH 8, 2022

I had previously worked at Xactly for 5 years (who went public) and Host Analytics for 6 years (got purchased) and was looking for a similar environment. Since launching in 2012, the company has seen explosive growth, and our data intelligence platform is used by more than 50 Fortune 100 companies today.

Sales 52

Sales Data Processing Finance Metrics 52

Smart Data Collective

APRIL 5, 2019

For example, it hones in on metrics in social media like retweets, engagement rates, mention, and story completions. Its goal was to “turn anonymous social media audiences into qualified prospects for sales and marketing” and the company raised $300,000 from a VC firm in 2012.

Big Data 79

Big Data Interactive Data-driven Metrics 79

Cloudera

AUGUST 6, 2018

This is important because unlike diabetes or high blood pressure we don’t yet have clear metrics for Parkinson’s. Data analytics and machine learning can help organizations to automate tasks in areas like fundraising or program management, among others, and thus free up needed time and money for other activities.

Machine Learning 50

Machine Learning Internet of Things Cost-Benefit Data-driven 50

AWS Big Data

MARCH 21, 2024

In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation of the zero-ETL series that started with Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift.

Data Warehouse 88

Data Warehouse Metrics Statistics Optimization 88

Juice Analytics

MARCH 3, 2021

www.forbes.com/special-report/2012/annoying-business-jargons-12.html. Reduce metrics. Most organizations are tempted to show as many metrics as possible, but it becomes impossible to understand and focus on everything at once. Create constraints to show only the metrics that matter most. Reduce pie charts.

Visualization 126

Visualization Metrics Dashboards Measurement 126

Sisense

MAY 26, 2020

Here’s what sample text data might look like: “Sisense is a business analytics software company with offices in New York City, San Francisco, Tel Aviv, London, Melbourne, Tokyo, Kiev, and Scottsdale, Arizona. Amit Bendov was appointed CEO in July 2012.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

AWS Big Data

JANUARY 22, 2024

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. Acast used the Well-Architected Framework for the central account to improve its practice running analytical workloads in the cloud.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

AWS Big Data

OCTOBER 19, 2023

Customers uploading and searching through decades of photos helped turn search into critical infrastructure, growing steadily since SmugMug first used Amazon CloudSearch in 2012, followed by Amazon OpenSearch Service since 2018, after reaching billions of documents and terabytes of search storage.

Publishing 55

Publishing Testing Cost-Benefit Data-driven 55

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 82

Machine Learning Metrics Big Data Management 82

Occam's Razor

DECEMBER 3, 2012

Use those metrics to optimize your social existence. Bonus: Are you tracking all the goals in your web analytics tool? Bonus: Facebook Advertising / Marketing: Best Metrics, ROI, Business Value. Do you have a 2009, 2012, 2015 mobile strategy? Your mobile strategy is ready for 2012. display strategy. Good question.

Marketing 147

Marketing Advertising Strategy Optimization 147

Domino Data Lab

JUNE 2, 2019

And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. I recall a “Data Drinkup Group” gathering at a pub in Palo Alto, circa 2012, where I overheard Pete Skomoroch talking with other data scientists about Kahneman’s work.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Domino Data Lab

JULY 22, 2019

You know, case in point, if you were to talk about predictive analytics 20 years ago, the main people in the field would have laughed you out of the room. Predictive analytics, yeah, not so much.” Those workflows would feedback into your business analytics. They would’ve said, “You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

MARCH 3, 2019

Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019). What metrics are used to evaluate success? Companies are applying AI in functional areas in which they likely have existing analytic applications, building atop that base. Who builds their models? One-third use human-in-the-loop.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Occam's Razor

SEPTEMBER 21, 2015

We send out our multi-tab spreadsheets, our best Google Analytics custom reports , our great dashboards full of data , and more to the tactical layer of data clients. We added to your analytical skills a demand for business savvy. Second, between 2012 and 2013. In fact 86.4% It is really 88%. : ). The reason is quite simple.

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Occam's Razor

SEPTEMBER 4, 2012

Google Analytics Mobile Application Analytics Suite ]. You can use your standard web analytics tool to measure customer behavior on your mobile-friendly website. Mobile application analytics solutions provide a very robust set of data about your apps. Everything described above is measureable.

Marketing 144

Marketing Data mining Measurement Strategy 144

Sisense

DECEMBER 11, 2019

An exciting slate of presentations took them on a journey from why to how they should use data analytics to optimize their operations successfully and maximize their business opportunities. There are plenty of opportunities for startups, but huge challenges too, with more than 50 percent of US startups failing to last longer than four years.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

This post describes the analytical issues which arise in such a setting, and what the data scientist can do about them. With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. And for good reason!

Experimentation 61

Experimentation Testing Statistics Metrics 61

datapine

MAY 17, 2021

Without a doubt, the best way to drive maximum value from the metrics, insights, and information is through something called data discovery. This level of discovery can be described and categorized by: Data preparation Visual analysis Guided advanced analytics. What Is Data Discovery? But how do you begin adopting this mentality?

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

Domino Data Lab

SEPTEMBER 9, 2019

This article and paired Domino project provide a brief introduction to working with natural language (sometimes called “text analytics”) in Python using spaCy and related libraries. Let’s analyze text data from the party conventions during the 2012 US Presidential elections. Introduction. for a, b in pairs:?.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110