CIO Business Intelligence

MAY 16, 2023

higher [in 2022] than in 2017.” The inherent capabilities of AI–to process vast amounts of data and use learned intelligence to make decisions with extraordinary speed–enable opportunities uncovered through digital listening. McKinsey & Company’s 2022 Global Survey on AI says , “AI adoption globally is 2.5x

Advertising 89

Advertising Recreation/Entertainment Experimentation Enterprise 89

Smart Data Collective

APRIL 5, 2022

Although SageMaker has become a popular hardware accelerator since it was launched in 2017, there are plenty of other overlooked hardware accelerators on the market. If you want to streamline various parts of the data science development process, then you should be aware of all of your options.

Cost-Benefit 122

Cost-Benefit Machine Learning Data Science Unstructured Data 122

Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. Derman (2016), Cesa (2017) & Bouchard (2018)).

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

IBM Big Data Hub

JULY 19, 2023

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. Content creation : Personas, user stories, synthetic data, generating images, personalized UI, marketing copy, email and social responses and more.

Consulting 59

Consulting Machine Learning Manufacturing Optimization 59

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. Many businesses use different software tools to analyze historical data and past patterns to forecast future demand and trends to make more accurate financial, marketing, and operational decisions.

Forecasting 85

Forecasting Data Warehouse Machine Learning Modeling 85

Smart Data Collective

JANUARY 13, 2021

Big data has started to change the world in a lot of ways. quintillion bytes of data every single day. As scalability with big data accelerates, consumers and organizations around the world are starting to witness its impact. Every aspect of our lives has been shaped by big data to some degree.

Big Data 86

Big Data Machine Learning Data-driven Manufacturing 86

Smart Data Collective

FEBRUARY 11, 2021

Big data has played a key role in driving the future of this budding niche. The pandemic has also pushed consumers towards online channels, with a global average of 58% of customer interactions being partially or fully digital as of July 2020, compared to 36% in December 2019. So, how can they go about maximizing this potential?

Marketing 80

Marketing Data Analytics Management Analytics 80

datapine

MAY 11, 2022

Digital data not only provides astute insights into critical elements of your business but if presented in an inspiring, digestible, and logical format, it can tell a tale that everyone within the organization can get behind. Data visualization methods refer to the creation of graphical representations of information. d) Area chart.

Visualization 252

Visualization Dashboards Key Performance Indicator Sales 252

datapine

NOVEMBER 19, 2019

If you don’t pay attention to new changes or keep up the pace, it’s easy to fall behind the times (and the market) while other companies beat you to the punch. For businesses looking to improve their consumer marketing communications, finding relevant images in real-time is a time-consuming venture. billion in 2017 to $190.61

Technology 279

Technology Internet of Things IT IoT 279

Occam's Razor

MAY 2, 2017

The very best analysts are know what matter’s the most are not the insights from big data but clear actions and compelling business impact from usually a smaller subset of key data. If your dashboards are CDPs (customized data pukes) do this every three months. I absolutely hate how not data driven most B2B selling is.

Metrics 141

Metrics Key Performance Indicator B2B Measurement 141

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ There’s an interesting narrative arc on the Google research blog between the 2009 paper “ The Unreasonable Effectiveness of Data ” and the 2017 update “Revisiting the Unreasonable Effectiveness of Data.”

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

SEPTEMBER 15, 2014

If you look at the mobile marketing strategies, you will see they don't reflect this shift to mobile. If you are in a feature phone majority market, and that market has most of the monetizable behavior, please invest in unique tracking there. For the first couple of interactions, give her/him that data.

Metrics 141

Metrics Reporting Analytics Marketing 141

The Data Visualisation Catalogue

DECEMBER 23, 2018

One of the methods I used during my investigatation into the impact of Virtual Reality (VR) technology on data visualization and infographic design was to simply search online what other people have been saying. Is there a chance that a lot of the marketers promoting data visualization in VR are spreading misinformation around?

Visualization 42

Visualization Big Data Finance Technology 42

Domino Data Lab

AUGUST 8, 2019

following a breakthrough paper or two, plus changes in market microstructure). to join data science teams, e.g., to support advertising, social networks, gaming, and so on—I hired more than a few. 2018 – Global reckoning about data governance, aka “Oops! Public Health Reports (2017-07-10). Or something.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Domino Data Lab

FEBRUARY 4, 2019

People who attended JupyterCon 2017–2018 can attest, an “industry poster session” includes an open bar, catered hors d’oeuvres, lots of mingling … to paraphrase feedback from JupyterCon, “As a tech person, would I get up extra early to meet strangers for coffee at 8:00 am? Katherine Twomey, Gert Westermann (2017). This is not that.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Peter James Thomas

AUGUST 12, 2018

It is entirely feasible that some market event occurs this year ( for example the entrance or exit of a competitor, or the launch of a new competitor product) which would render prior year figures a poor guide. Ideas for avoiding Big Data failures and for dealing with them if they happen (2017). Follow @peterjthomas.

Metrics 49

Metrics Statistics Data Quality Measurement 49

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Over the past decade, business intelligence has been revolutionized.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

DataRobot Blog

OCTOBER 3, 2017

With this integration, customers can now harness the full power of Azure’s Big Data offerings in a self-service manner to gain immediate value.”. A Senior Director of Data Science for a marketing / advertising tech company is charged with television programming, content, creative, and message testing analysis.

Data Lake 52

Data Lake Data Architecture Advertising Insurance 52

O'Reilly on Data

JANUARY 25, 2021

The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. We’ve explored usage across all publishing partners and learning modes, from live training courses and online events to interactive functionality provided by Katacoda and Jupyter notebooks.

Machine Learning 363

Machine Learning Software Testing Technology 363

Occam's Razor

JULY 13, 2017

The sixteen examples neatly fall into nine strategies I hope you’ll cultivate in your analytics practice as you create data visualizations: 1: The Simplicity Obsession. 4: Interactivity With Insightful End-Points. 6: Turbocharging Data Visuals with Storytelling. Strategy 4: Interactivity With Insightful End-Points.

Visualization 124

Visualization Strategy Interactive Statistics 124