Cloudera

NOVEMBER 15, 2021

The word “data” is ubiquitous in narratives of the modern world. And data, the thing itself, is vital to the functioning of that world. This blog discusses quantifications, types, and implications of data. Quantifications of data. Quantifications of data. So data is big and growing.

Unstructured Data 85

Unstructured Data Recreation/Entertainment Structured Data Reporting 85

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? So it’s Monday, and you lead a data analytics team of perhaps 30 people. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. What should be in that report about your data team? Forty-five metrics! Introduction.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

Ontotext

DECEMBER 16, 2020

At the end of an unconventional year, we at Ontotext still want to honor our tradition and provide our readers with a round-up of the most popular posts on our blog. In its third generation, Ontotext Platform enables organizations to build, use and evolve knowledge graphs as a hub for data, metadata and content.

Metadata 52

Metadata Unstructured Data Visualization Enterprise 52

IBM Big Data Hub

JULY 26, 2023

The emergence of generative AI and foundation models has revolutionized the way every business, across industries, operates at this current inflection point. This is especially true in the HR function, which has been pushed to the forefront of the new AI era.

Digital Transformation 71

Digital Transformation Cost-Benefit Data-driven Strategy 71

IBM Big Data Hub

JULY 19, 2023

This digital data is coming at the industry in various formats, like unstructured text, images, PDFs and emails. The exponential leap in generative AI is already transforming many industries: optimizing workflows , helping human teams focus on value added tasks and accelerating time to market.

Consulting 66

Consulting Machine Learning Manufacturing Optimization 66

IBM Big Data Hub

AUGUST 28, 2023

Macmillan Publishers is a global publishing company and one of the “Big Five” English language publishers. It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. As business processes grew more complex, the data transparency and visibility suffered.

Publishing 55

Publishing Analytics Business Intelligence Operational Reporting 55

Cloudera

SEPTEMBER 9, 2021

The CDP Operational Database ( COD ) builds on the foundation of existing operational database capabilities that were available with Apache HBase and/or Apache Phoenix in legacy CDH and HDP deployments. Cloudera Machine Learning or Cloudera Data Warehouse), to deliver fast data and analytics to downstream components.

Cost-Benefit 91

Cost-Benefit Optimization Risk Management 91

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Analytics 65

Analytics Testing Metrics Management 65

Alation

JANUARY 30, 2023

Alation launched the Data Intelligence Project in summer 2021 to train the next generation of data leaders by providing learning opportunities with Alation in the classroom. In this blog, we’ll reveal how Professor McMahon encountered Alation and launched the program in his own school — and how he plans to develop it for the future.

Data Governance 52

Data Governance Metadata Data-driven Software 52

Sisense

JULY 8, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

Sisense

MARCH 26, 2021

Companies surveyed by Harvard Business Review Analytic Services (HBR) report that two of the most important strategic benefits of using data analytics are (1) identifying new revenue and business models and (2) becoming more innovative. 39% of companies want to identify new revenue and business opportunities with data analytics.

Analytics 98

Analytics Data-driven Dashboards Experimentation 98

AWS Big Data

JUNE 6, 2023

Data is the lifeblood of modern businesses. In today’s data-driven world, companies rely on data to make informed decisions, gain a competitive edge, and provide exceptional customer experiences. However, not all data is created equal. AWS Glue Data Quality measures and monitors the quality of your dataset.

Data Quality 66

Data Quality Data Lake Visualization Data-driven 66

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. What’s the reality? Certainly not two-thirds of them.

Enterprise 271

Enterprise Modeling Testing Reporting 271

Domino Data Lab

FEBRUARY 20, 2019

Eugene Mandel , Head of Product at Superconductive Health , recently dropped by Domino HQ to candidly discuss cross-team collaboration within data science. Eugene Mandel , Head of Product at Superconductive Health , recently dropped by Domino HQ to discuss cross-team collaboration within data science.

Data Science 76

Data Science Testing Software Uncertainty 76

datapine

MAY 31, 2022

2) The Challenges Of Cloud Computing. In this article, we have gathered the 12 most prominent challenges of cloud computing that will deliver fresh perspectives related to the market. In this article, we have gathered the 12 most prominent challenges of cloud computing that will deliver fresh perspectives related to the market.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

Insight

OCTOBER 25, 2019

Image credit: [link] As the title suggests, this is a story about a question that may resonate well with many machine learning practitioners trying to build applications in the real world, where clean and annotated data on a specific problem can be sparse— How do we leverage the power of AI when we have very little data?

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

Data Science 101

JANUARY 19, 2021

34:15 Is 2021 too late to start a blog? Start a Blog, Start and Podcast, You can do it! Stress-free Goal Setting with Deb Eckerling. Debra Eckerling is a goal-setting expert. She offers coaching, workshops, and online support for people looking to achieve goals in any aspect of life. Connect with Deb. Listen to the Audio. Great Advice.

Recreation/Entertainment 98

Recreation/Entertainment IT Management Data Science 98

Occam's Razor

APRIL 13, 2015

And, that's not all, when you consider that it is segmented data, across multiple dimensions, it really is impressive. But, I'm a big believer in optimizing data access to be at the right time as defined by your decision-making/action-taking speeds inside your company. This hurts my feelings!

Analytics 155

Analytics Reporting Metrics Slice and Dice 155

O'Reilly on Data

JULY 25, 2023

So far I’ve read a gazillion blog posts about people’s experiences with these AI coding assistance tools. Setting the Stage: Who Am I and What Am I Trying to Build? I’m a professor who is interested in how we can use LLMs (Large Language Models) to teach programming. This article summarizes what I learned from that experience.

Consulting 246

Consulting Interactive Software IT 246

The Unofficial Google Data Science Blog

APRIL 23, 2024

This blog post discusses such a comprehensive approach that is used at Youtube. This blog post discusses such a comprehensive approach that is used at Youtube. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Cloudera

JULY 26, 2021

With this first article of the two-part series on data product strategies, I am presenting some of the emerging themes in data product development and how they inform the prerequisites and foundational capabilities of an Enterprise data platform that would serve as the backbone for developing successful data product strategies.

Strategy 114

Strategy Marketing Data Science Unstructured Data 114

datapine

NOVEMBER 15, 2022

In an increasingly data-driven business world, the product management field isn’t exempt from this need. Online data analysis tools will help you sharpen your product sense and give more weight and credibility to the decisions you make and submit to stakeholders. And that’s where the big challenge lies. is essential.

Metrics 141

Metrics KPI Measurement Dashboards 141

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Companies, both big and small, are seeking the finest ways to leverage their data into a competitive advantage.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Occam's Razor

JANUARY 4, 2022

This blog post was originally published as an edition of my newsletter TMAI Premium. When I think of importance, I have five elements in mind. We can all use head fake metrics to calling out useless activity metrics. [ I would add other head fake KPIs to the list: Impressions. Cost Per View. Others of the same ilk. The law of God.

KPI 127

KPI Advertising Metrics Measurement 127

Cloudera

AUGUST 20, 2021

How CDP Enables and Accelerates Data Product Ecosystems. A multi-purpose platform focused on diverse value propositions for data products. As a result, CDP-enabled data products can meet multiple and varying functional and non-functional requirements that correspond to product attributes, each fulfilling specific customer needs.

Strategy 94

Strategy Cost-Benefit Visualization Data Warehouse 94

Sisense

NOVEMBER 30, 2020

Every company is becoming a data company. Data-Powered Apps delves into how product teams are infusing insights into applications and services to build products that will delight users and stand the test of time. The trend of converting data into profitable insights is now an industry in itself.

Analytics 98

Analytics Dashboards Metrics Data-driven 98

Cloudera

JUNE 14, 2021

How to optimize an enterprise data architecture with private cloud and multiple public cloud options? The Surging Importance of Data. Data has never been more important. Connectivity has become too critical to people’s lives to be compromised for a relatively small amount of cost difference.

Data Architecture 91

Data Architecture Enterprise Finance Strategy 91

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. This blog post introduces the notions of representational uncertainty and interventional uncertainty to paint a fuller picture of what the practicing data scientist is up against. This blog post does not discuss objectives.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

IBM Big Data Hub

NOVEMBER 20, 2023

Recent technological advancements in data storage have prompted businesses and consumers to move away from traditional hard disk drives (HDDs) towards faster, lower-latency solid-state drive (SSD) technology. NVMe SSDs For the fastest data transfer speeds available, look no further than the NVMe SSD. What is an SSD?

Internet of Things 72

Internet of Things Enterprise Technology IoT 72

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. No matter your skill, career level, or title, the ability to analyze, organize, and visualize data are vital skills in our world of quickly growing and ever-changing data. Statistical techniques to handle nontrivial data.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

Insight

MARCH 28, 2019

For the Fall 2018 session of the Insight Fellows Program in NYC, we launched a new partnership with Thinknum , a company that provides alternative data indexed from the web to institutional investors and corporations?—?think think online product listings, store location data, job listings, social media presence, and more?

Dashboards 70

Dashboards Visualization Data Science Machine Learning 70

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction. Yeah, not so much.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Cloudera

AUGUST 21, 2021

There is an urgent need for banks to be nimble and adaptable in the thick of a multitude of industry challenges, ranging from the maze of regulatory compliance, sophisticated criminal activities, rising customer expectations and competition from traditional banks and new digital entrants. Addressing new customers and markets.

Data-driven 98

Data-driven Digital Transformation Risk Risk Management 98

CDW Research Hub

OCTOBER 12, 2021

Creating a modern data platform designed to support your current and future needs is critical in a data-driven organization. Business leaders need to quickly access data—and to trust the accuracy of that data—to make better decisions. Unreliable Data as a Service (DaaS) implementations.

Data Warehouse 52

Data Warehouse Big Data Data Architecture Cost-Benefit 52

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. And you also already know siloed data is costly, as that means it will be much tougher to derive novel insights from all of your data by joining data sets.

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. What can analysts do, if anything, to overcome the multi-device challenge. Then you build a massive data store that you can query for data to analyze. EU Cookies!)

Modeling 124

Modeling Metrics Data Quality Data-driven 124