AWS Big Data

SEPTEMBER 22, 2023

In our infrastructure, Apache Kafka has emerged as a powerful tool for managing event streams and facilitating real-time data processing. If you’d like to know more background about how we use Kafka at Stitch Fix, please refer to our previously published blog post, Putting the Power of Kafka into the Hands of Data Scientists.

Management 119

Management Metrics Cost-Benefit Data Lake 119

CIO Business Intelligence

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. Ever wonder why an internet search for a product reveals similar prices across competitors, or why surge pricing occurs?

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

Occam's Razor

OCTOBER 12, 2017

With that context, this post is all about career management in the digital space. Like this blog, it will be particularly relevant for those who are in digital analytics and digital marketing. Your employer/manager would help you figure out the skills you can develop, this is for the most part no longer true. I learned a lot.

Marketing 138

Marketing Analytics Machine Learning Strategy 138

Cloudera

OCTOBER 11, 2022

Al needs machine learning (ML), ML needs data science. He goes on to say “The key lesson in all of this is to think of AI as a learning-based system.” It’s also about how to use data anywhere to provide the most complete and up-to-date picture for the AI systems as they continue to learn and evolve. .

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

Cloudera

NOVEMBER 9, 2022

As part of Cloudera’s professional services team, Timur is a senior manager of professional services strategy, serving Cloudera’s public sector customers in federal, state, and local governments, as well as higher education. . “A And analytics is a prerequisite to be able to do machine learning or artificial intelligence of any kind.

Strategy 88

Strategy Management Consulting Machine Learning 88

Timo Elliott

JANUARY 5, 2022

This is a English translation of an article by Thérèse van Bellinghen that first appeared on the SAP News Blog. . Yves Lombaerts, Sales Manager for the Belgian market, picked up our Global Innovation Evangelist Timo Elliott for an interesting ride to SAP’s offices in Brussels. What is your concrete role at SAP?

Digital Transformation 115

Digital Transformation Machine Learning Enterprise Data Science 115

Timo Elliott

JANUARY 3, 2020

This is a copy of a blog post that appeared in Digitalist Magazine , ably assisted by Shelly Dutton. . If any lessons were learned over the last decade, one of them is undoubtedly that technology innovation has leveled the playing field for businesses of all sizes. Why do I say “unfortunately”?

Key Performance Indicator 77

Key Performance Indicator Machine Learning Digital Transformation Strategy 77

Cloudera

NOVEMBER 24, 2020

Judge of the Data Champions category, Bob Gorley, co-founder and Chief Technology Officer of technology research and advisory firm, OODA LLC shared his views about the category and nominees on the night, saying: ‘Every nominee we saw had fielded a great solution that we all ought to take note of and learn lessons from.

Insurance 74

Insurance Marketing Risk Machine Learning 74

IBM Big Data Hub

APRIL 24, 2023

Companies realized that their legacy or enterprise data warehousing solutions could not manage the huge workload. Innovative organizations sought modern solutions to manage larger data capacities and attain secure storage solutions, helping them meet consumer demands. Enter the modernization of data warehousing solutions.

Data Warehouse 88

Data Warehouse Data Lake Cost-Benefit Big Data 88

Cloudera

SEPTEMBER 29, 2021

Without a data-driven strategy, you’re bound to lose ground to competitors who apply their data to operational improvements, product development, go-to-market strategies, and the customer experience. Before mid-size firms can start spending on data management platforms and analytics tools, they seek assurances of a pay-off.

Data-driven 79

Data-driven Data Collection Strategy Enterprise 79

Alation

FEBRUARY 3, 2022

They make testing and learning a part of that process. The car manufacturer leverages kaizen to improve productivity. The goal of DataOps is to create predictable delivery and change management of data and all data-related artifacts. Data governance is a key data management process. Subscribe to Alation's Blog.

Data Governance 98

Data Governance Measurement Metadata Testing 98

Ontotext

JUNE 10, 2021

This is a graph of millions of edges and vertices – in enterprise data management terms it is a giant piece of master/reference data. Removing ungainly representation was an early lesson learned by the pioneers of the Semantic Web when Description Logics (DL) were a prevalent approach in the field. It can be queried.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

CDW Research Hub

NOVEMBER 12, 2020

In fact, most companies have a long line of AI use cases identified, in development, or already in productive use. The first business lesson many companies learn the hard way is that AI projects are iterative and never-ending. Compute where the data lives. The location of the data should influence where it is processed.

ROI 79

ROI Deep Learning Machine Learning Business Objectives 79

Cloudera

DECEMBER 7, 2020

There are lessons to be learned from the brick and mortar or pure-play digital retailers that have been successful in the Covid-19 chaos. This blog is a first in a series that will examine the pillars and the successful customer case studies that have resulted. How a leading global drug store improved precision and timeliness.

Cost-Benefit 62

Cost-Benefit Interactive Unstructured Data Big Data 62

Domino Data Lab

JULY 28, 2021

For companies creating models to scale, an enterprise Machine Learning Operation (MLOps) platform not only needs to support enterprise-grade development and production, it needs to follow the same standard process that data scientists use. DSLC can be divided into four steps or stages: Manage, Develop, Deploy and Monitor.

Data Science 59

Data Science Enterprise Modeling Experimentation 59

Sisense

DECEMBER 11, 2019

With data growing at a staggering rate, managing and structuring it is vital to your survival. In our Event Spotlight series, we cover the biggest industry events helping builders learn about the latest tech, trends, and people innovating in the space. In this piece, we detail the Israeli debut of Periscope Data.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

Cloudera

AUGUST 1, 2023

Meet Shallan Miller Shallan is a Senior Marketing Events Manager at Cloudera. She manages a wide range of internal and external events. After the team’s creation, they set out to build a best-in-class events machine. I went about building our house in the same way I project manage events. You name it, I’ve worked on it.”

Marketing 64

Marketing Sales Testing Management 64

Alation

JULY 28, 2021

While governance has been a major focus for many years when it comes to managing data, governance focused on data science processes is still far less mature. This blog will discuss a couple of distinct areas of governance that organizations should consider. Yet, people are still comfortable that Coke products are safe to enjoy.

Data Science 52

Data Science Data Governance Modeling Software 52

Alation

JULY 30, 2021

In Key Takeaways from ‘The Qualified Sales Leader’, I shared that salespeople must sell product value over feature and function if they wish to excel. This is a painful lesson for many organizations, who have a lingering mess of data… and no real means to rationalize it.

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

Occam's Razor

JULY 24, 2018

On this blog, you’ve seen numerous attempts by me to remedy the dilemma. Analyzing these metrics not only fundamentally changes marketing strategy (think tens of millions of dollars for large companies); their insights can change your company’s product portfolio, your customer engagement strategies and much more.

Analytics 95

Analytics Metrics Strategy Measurement 95

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. What shipping route is the most fuel efficient?

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Ontotext

JANUARY 21, 2021

The Financial Industry Business Ontology (FIBO) is a standard that is being developed and published by the Enterprise Data Management Council that attempts to capture business domain knowledge using sophisticated knowledge representation techniques and linked open data technologies. Introduction. This is a nontrivial task.

Modeling 72

Modeling Finance Technology Publishing 72

Domino Data Lab

JULY 22, 2019

This blog post provides a concise session summary, a video, and a written transcript. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Occam's Razor

JANUARY 10, 2011

Let's start off the new year with lessons learned from a tough life on the front lines of trying to make the world a smidgen more data-driven. These lessons might have made some goals easier to accomplish, some frustrations easier to avoid and some salary jumps easier to come by. Great lesson. Stop switching tools!

Analytics 121

Analytics Measurement Data-driven Optimization 121

Occam's Razor

AUGUST 28, 2017

Over the last couple years, I’ve spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). You’ll learn all about the Global Maxima, definitions of AI/ML/DL, and the implications related to the work we do day to day. Here’s the video….

Deep Learning 140

Deep Learning Machine Learning Marketing Strategy 140

IBM Big Data Hub

FEBRUARY 14, 2024

AI is not yet loading the dishwasher after supper—but can help create a legal brief, a new product design, or a letter to grandma. Here are 27 highly productive ways that AI use cases can help businesses improve their bottom line. We’re all amazed by what AI can do.

Cost-Benefit 82

Cost-Benefit Insurance Machine Learning Unstructured Data 82

Cloudera

APRIL 21, 2022

military and kept track of health records for millions of active-duty soldiers, sailors, airmen and airwomen, support staff, and retired service people using pens & pencils, typewriters, paper, carbon paper, copy machines, and snail-mail. So how exactly is the EHR managing petabytes of data?

Informatics 87

Informatics Metadata Insurance Data Processing 87

Occam's Razor

APRIL 30, 2018

I cannot stress enough that these results can be positive (for the ad business and, in this case, the sales of insurance products). The further sub-sub-segmentation into products and services (depending on the company). Companies add layers upon layers to manage. Your internal marketing or product teams?

Advertising 118

Advertising Metrics Measurement Insurance 118

Ontotext

NOVEMBER 11, 2024

Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. Organizations already know the data they need to manage is too diverse, dispersed, and at volumes unfathomable only a decade ago.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52

O'Reilly on Data

APRIL 15, 2025

But after helping 30+ companies build AI products, Ive discovered that the teams who succeed barely talk about tools at all. This brings us to another counterintuitive lesson: The people best positioned to improve your AI system are often the ones who know the least about AI. Instead, they obsess over measurement and iteration.

Experimentation 332

Experimentation Testing Metrics Measurement 332