CIO Business Intelligence

JUNE 29, 2022

Many lack the necessary quality of data, or the financial resources and internal talent to speedily turn that data into reliable, relevant insights. They move from manual to automated data wrangling, to deliver results in an easy-to-view format, achieve consistency and limit errors.

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Predictive Analytics Analytics Data-driven Forecasting 137

datapine

MAY 14, 2019

“Big data is at the foundation of all the megatrends that are happening.” – Chris Lynch, big data expert. We live in a world saturated with data. Zettabytes of data are floating around in our digital universe, just waiting to be analyzed and explored, according to AnalyticsWeek. Wondering which data science book to read?

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Data Science Machine Learning Data-driven Big Data 350

Data Science 101

MAY 23, 2019

Here is the latest data science news for May 2019. From Data Science 101. REAL TALK WITH A DATA SCIENTIST: THE FUTURE OF DATA WRANGLING WHAT IS ON THE MICROSOFT DATA SCIENCE CERTIFICATION EXAM? General Data Science. Not all are data science/AI related, but many are. This is exciting.

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CIO Business Intelligence

DECEMBER 26, 2023

This knowledge wrangling — and ignorance vanquishing — operation could work at a departmental or group level and rotate around the staff on an episodic basis. In many communities, December is a month set aside for reflection. Such exercises are valuable but anachronistic. Here’s what that means and how to achieve it.

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Uncertainty Technology Forecasting Strategy 110

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 86

Data Science Data Analytics Prescriptive Analytics Analytics 86

3AG Systems

DECEMBER 8, 2022

Is Data Scientist still the sexiest job of the 21 st century ? When the Data Scientist role “was relatively new” in 2012, the authors observed that “as more companies attempted to make sense of big data, they realized they needed people who could combine programming, analytics, and experimentation skills.” Read More

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Data Science Experimentation Machine Learning Big Data 40

CIO Business Intelligence

JULY 18, 2023

Nvidia’s transformation from an accelerator of video games to an enabler of artificial intelligence (AI) and the industrial metaverse didn’t happen overnight—but the leap in its stock market value to over a trillion dollars did. The once-niche chipmaker, now a Wall Street darling, was becoming a household name.

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Manufacturing Forecasting Software Marketing 98

The Data Visualisation Catalogue

FEBRUARY 16, 2023

In the previous post , I explored how useful ChatGPT currently is for data visualisation. This was done through testing this AI tool on a number of tasks and on its information retrieval ability. But if ChatGPT and other AI tools like it continue to improve, what impact will they have in the future for DataViz work?

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Dashboards Consulting Machine Learning Technology 122

AWS Big Data

NOVEMBER 13, 2023

For those in the data world, this post provides a curated guide for all analytics sessions that you can use to quickly schedule and build your itinerary. A shapeshifting guardian and protector of data like Data Lynx? Or a digitally clairvoyant master of data insights like Cloud Sight?

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Analytics Data Lake Data Warehouse Data-driven 112

IBM Big Data Hub

APRIL 28, 2022

Data agility, the ability to store and access your data from wherever makes the most sense, has become a priority for enterprises in an increasingly distributed and complex environment. That’s where the data fabric comes in. Data fabric in action: Retail supply chain example. enterprises to minimize their time to value.

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Metadata Data Warehouse Forecasting Predictive Modeling 88

AWS Big Data

MARCH 26, 2024

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Smart Data Collective

JUNE 20, 2023

We have talked about some of the major changes that big data and artificial intelligence have brought to Google. This includes the growing number of people that rely on AI technology to use Google Sheets. This includes the growing number of people that rely on AI technology to use Google Sheets. That’s where AI steps in!

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Software Machine Learning Visualization Interactive 56

DataRobot

JANUARY 13, 2022

Many companies find that they have a treasure trove of data but lack the expertise to use it to improve ROI. AI can help them wrangle the data that’s collected and quickly answer important questions. But they often don’t have enough data scientists with the full range of domain expertise to realize its full value.

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ROI Machine Learning Experimentation Data Science 52

Jet Global

NOVEMBER 20, 2023

Unlock insights from ERP Data to Deliver Actionable Insights Let’s face it. The valuable data stored in your ERP system can help you make informed decisions, but that data is often the toughest to unlock. It’s simple – the famous “ 80/20 data science dilemma ” explains it best.

Business Intelligence 52

Business Intelligence IT Operational Reporting Reporting 52

O'Reilly on Data

OCTOBER 16, 2018

Create a coherent BI strategy that aligns data collection and analytics with the general business strategy. They recognize the instrumental role data plays in creating value and see information as the lifeblood of the organization. These problems are further compounded as companies move to adopt more sophisticated data science and AI.

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Business Intelligence Data Science Descriptive Analytics Strategy 149

Cloudera

FEBRUARY 8, 2021

Within the vehicle, current electronics and wiring infrastructures were not designed for this complex data wrangling capability. In addition, moving outside the vehicle, existing fragmented approaches for data management associated with the machine learning lifecycle are limiting the ability to deploy new use cases at scale.

Machine Learning 107

Machine Learning Manufacturing Unstructured Data Modeling 107

Sisense

AUGUST 14, 2020

In Augmented Apps , we examine how product teams are exploring AI and Machine Learning to make their products more intuitive and enhance the user experience. . Certain proven methods and use cases are invaluable in helping product teams understand how to implement AI in apps to reproduce and enhance existing successes.

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Machine Learning Visualization Predictive Analytics Testing 98

AWS Big Data

NOVEMBER 10, 2023

Apache Spark is a widely-used open source distributed processing system renowned for handling large-scale data workloads. Amazon Redshift offers seamless integration with Apache Spark, allowing you to easily access your Redshift data on both Amazon Redshift provisioned clusters and Amazon Redshift Serverless.

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CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Sisense

JANUARY 22, 2021

That advice is a quintessential actionable insight: The algorithm models the applicant’s probability of success by training on a mountain of historical data and market factors. In every industry, actionable insights arising from analytics and AI are no longer a luxury, but a necessity for achieving competitiveness.

Machine Learning 52

Machine Learning Unstructured Data Forecasting Advertising 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

AUGUST 28, 2023

It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. For more than 10 years, the publisher has used IBM Cognos Analytics to wrangle its internal and external operational reporting needs. As business processes grew more complex, the data transparency and visibility suffered.

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Publishing Analytics Business Intelligence Operational Reporting 56

AWS Big Data

SEPTEMBER 29, 2023

In today’s digital age, data is at the heart of every organization’s success. One of the most commonly used formats for exchanging data is XML. Analyzing XML files can help organizations gain insights into their data, allowing them to make better decisions and improve their operations.

Metadata 67

Metadata Visualization Data-driven Optimization 67

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

Domino Data Lab

MAY 8, 2019

Several technology conferences all occurred within four fun-filled weeks: Strata SF , Google Next , CMU Summit on US-China Innovation, AI NY , and Strata UK , plus some other events. For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

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Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction. Ever heard of it before?

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Data Science Machine Learning Data Governance Statistics 71

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.

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Data Science Experimentation Data-driven Machine Learning 66

CIO Business Intelligence

AUGUST 15, 2023

2023 has been a break-out year for generative AI technology, as tools such as ChatGPT graduated from lab curiosity to household name. But CIOs are cautiously evaluating how to safely deploy generative AI in the enterprise, and what guard-rails to put around it.

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Software Enterprise Sales Visualization 98

CIO Business Intelligence

AUGUST 25, 2023

AI never sleeps. With every new claim that AI will be the biggest technological breakthrough since the internet, CIOs feel the pressure mount. Some are basic: What is generative AI? Others are more consequential: How do we diffuse AI through every dimension of our business? You can’t wrangle AI by yourself.

Strategy 98

Strategy Data Strategy Experimentation Uncertainty 98

Alation

FEBRUARY 20, 2020

We are living in a new era of data defined by two massively disruptive trends – one architectural and the other organizational. Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. A “big data” revolution has ensued.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

IBM Big Data Hub

MAY 12, 2022

To navigate this constantly disrupted world, clients need more data, more collaboration and more assurances that they can act at the speed of business without risk. In fact, everyone, at all levels, need to be data-driven to face this disruptive new reality. For example: What is in the way of making better decisions?

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Business Analytics Analytics Recreation/Entertainment Cost-Benefit 57

CONTACT Software

FEBRUARY 19, 2019

The idea of platforms for automatic data analysis comes at just the right time. However, data science is not an area where you can magically get ahead with a tool or even a platform. A look at data science online tutorials from top providers like Coursera underlines the importance of these – well – down-to-earth tools.

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Data Science Statistics Machine Learning Deep Learning 40

Alation

APRIL 2, 2021

Three new case studies from Alation have exciting implications for the world of data management. The Time Is on My Side case studies examine major pain points for data-centric enterprises. Recently I sat down with the study authors and data scientists at Alation, Andrea Levy and Naveen Kalyanasamy. What was your approach?

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Measurement Metadata Data Science Machine Learning 52

CIO Business Intelligence

JUNE 29, 2022

Businesses will move from data to science. For years, businesses have focused on identifying and wrangling credible valuable data sources. This is resulting in an overabundance of data. While data scientists will become ever more important to businesses, core predictive analytics will also become accessible to all teams.

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Predictive Analytics Analytics Business Objectives Data-driven 120

Cloudera

AUGUST 26, 2020

On August 18, we completed our Enterprise Data Cloud vision of bringing a truly hybrid cloud experience with the general availability of Cloudera Data Platform Private Cloud (CDP Private Cloud). Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information.

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Machine Learning Big Data Data Warehouse Data-driven 82

Sisense

JUNE 15, 2021

Marketing can be one of the most data-driven departments in a company, regardless of industry. That being said, not every marketing org is making the best use of the data at its disposal. Optimize your data workflow for more successful growth marketing. Starting at the top: Driving your marketing strategy with data.

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Analytics Data-driven Marketing Key Performance Indicator 52