Smart Data Collective

NOVEMBER 18, 2020

You should learn what a big data career looks like , which involves knowing the differences between different data processes. Online courses and universities are offering a growing number of programs of study that center around the data science specialty. What is Data Science? Where to Use Data Science?

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Data mining Data Science Informatics Statistics 143

Cloudera

SEPTEMBER 10, 2020

Cloudera has been named a Leader in The Forrester Wave : Notebook-Based Predictive Analytics and Machine Learning, Q3 2020. This means that both IT teams and data science teams can seamlessly work together to accelerate time to value for machine learning workflows — no more data silos, security issues, or cross-team slowdowns.

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Machine Learning Predictive Analytics Analytics Enterprise 97

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Smart Data Collective

NOVEMBER 7, 2019

The benefits of predictive analytics for businesses are numerous. However, predictive analytics can be just as valuable for solving employee retention problems. Towards Data Science discusses some of the benefits of predictive analytics with employee retention.

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Predictive Analytics Analytics Cost-Benefit Risk 47

Smarten

DECEMBER 17, 2018

Tools like Assisted Predictive Modeling allow the average business user to become a Citizen Data Scientist with tools that offer guidance and auto-suggestions to help the user arrive at the outcome they need without being frustrated or having to call in an army of analysts and IT staff to help them complete their analysis.

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Predictive Analytics Predictive Modeling Analytics Statistics 40

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

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Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Its value is so significant that scaling data science has become the new business imperative with organizations spending tens of millions of dollars on data, technology and talent. Data Science Techniques.

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Data Science Machine Learning Statistics Deep Learning 45

IBM Big Data Hub

AUGUST 7, 2023

Therefore, IBM observes that more clients tend to consult AI leaders to help establish governance and enhance AI and data science capabilities, an operating model in the form of co-delivery partnerships. AI models can be designed to detect anomalies in real-time site performance data. Clinical Trials. 2019;16(2):183-193.

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Optimization Forecasting Data-driven Strategy 55

Domino Data Lab

JANUARY 24, 2019

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. Over the last couple years, it would be hard to blame anyone for being overwhelmed looking at the data science platform market landscape. Proprietary (often GUI-driven) data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

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Data Architecture Data Warehouse Statistics Visualization 129

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. How to prepare: No prior computer science or programming knowledge is necessary.

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Big Data Data Analytics Analytics Predictive Modeling 124

CIO Business Intelligence

OCTOBER 1, 2022

The digital transformation of P&G’s manufacturing platform will enable the company to check product quality in real-time directly on the production line, maximize the resiliency of equipment while avoiding waste, and optimize the use of energy and water in manufacturing plants. Smart manufacturing at scale is a challenge. “We

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Smart Data Collective

JANUARY 27, 2021

A number of new predictive analytics algorithms are making it easier to forecast price movements in the cryptocurrency market. Conversely, if predictive analytics models suggest that the value of a cryptocurrency price is likely to decrease, more investors are likely to sell off their cryptocurrency holdings.

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Machine Learning Forecasting Predictive Analytics Marketing 138

Cloudera

OCTOBER 4, 2023

We can also increase effectiveness of preventative maintenance — or move to predictive maintenance — of equipment, reducing the cost of downtime without wasting any value from healthy equipment. In financial services, fast-moving data is critical for real-time risk and threat assessments. Ready to stop blinking and never miss a beat?

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Data Warehouse Experimentation Cost-Benefit Dashboards 91

Cloudera

APRIL 9, 2021

The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. And this blog will focus on Predictive Analytics. Data Collection – streaming data. Data Enrichment – data engineering. The ML Challenge.

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Machine Learning Forecasting Manufacturing Predictive Analytics 98

DataRobot Blog

MARCH 8, 2023

As a result, enterprises can now get powerful insights and predictive analytics from their business data by integrating DataRobot-trained machine learning models into their SAP-specific business processes and applications, while bringing data science and analytics teams and business users closer together for better outcomes.

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CIO Business Intelligence

NOVEMBER 14, 2022

With organizations increasingly focused on data-driven decision making, decision science (or decision intelligence) is on the rise, and decision scientists may be the key to unlocking the potential of decision science systems. Optimization analysis models. Analytics, Data Science Model-driven DSS.

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Data mining Data-driven Statistics OLAP 133

CIO Business Intelligence

JUNE 1, 2022

Like professional basketball, industrial-scale farming, national politics, and global merchandising, auto racing has become a data science. The data transmitted from each car during a race ? Predictive analytics can foretell a breakdown before it happens. A Competitive Differentiator.

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Manufacturing Digital Transformation Predictive Analytics Strategy 104

FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. SQL manages and retrieves data from databases, handling larger datasets.

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Statistics Data mining Visualization Reporting 52

Cloudera

JANUARY 5, 2021

Website Operations —Analyze website operations to improve efficiencies in order fulfillment service levels, optimize delivery options offered. Consolidated Inventory & Sales Data — Build an enterprise view of sales and inventory across all channels.

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Forecasting Cost-Benefit Sales Unstructured Data 93

Smart Data Collective

AUGUST 10, 2021

. ‘Although companies in healthcare, IT and finance are some of the biggest investors in analytics technology, plenty of other sectors are investing in analytics as well. Analytics Becomes Major Asset to Companies Across All Sectors. Do you find storing and managing a large quantity of data to be a difficult task?

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CIO Business Intelligence

JULY 31, 2023

To keep up with the unsettling pace, Swiss Re, one of the world’s largest reinsurers, now leverages predictive analytics, machine learning (ML), and artificial intelligence (AI) to help its clients anticipate disasters and mitigate costs. “If In 2023, through July 11, NOAA confirmed 12 such events, including floods and severe storms.

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Insurance Strategy Modeling Data-driven 87

Smarten

JANUARY 15, 2019

No complex algorithms or data manipulation. Auto-recommendations for algorithms to explore underlying data without advanced knowledge. No advanced data science skills required. Analyze, share and optimize business potential. Business users can prototype and hypothesize without professional assistance.

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Predictive Modeling Modeling Forecasting Predictive Analytics 40

Data Science 101

OCTOBER 31, 2019

Therefore, learning some useful data mining procedures may prove beneficial in this regard. As taught in Data Science Dojo’s data science bootcamp , you will have improved prediction and forecasting with respect to your product. Data Mining Process. Regression.

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Data mining KDD Data Science Forecasting 77

Birst BI

AUGUST 23, 2018

Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases?

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Machine Learning Data Science Testing Metrics 73

Smarten

APRIL 25, 2024

Key Influencer Analytics employs machine learning and auto-recommendations to identify both the target and the influencers and allow users to interact with the tools to reveal and understand the impact of influencers and focus on variables that matter most to the target.

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Data Quality Analytics Machine Learning Visualization 62

Smart Data Collective

JULY 24, 2023

billion on analytics last year. Nabil M Abbas of Towards Data Science talked about one of the most interesting ways that data analytics is changing the NBA. Abbas states that more players are attempting three-point shots based on analytics findings. a year until 2030.

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Analytics Technologies Marketing Technology Analytics 79

Smarten

AUGUST 1, 2022

For example, a retail store manager may want to analyze the optimal and strategic placement of various products in order to increase cross sales. For a business to succeed in transforming business users to Citizen Data Scientists, it must have a firm grasp on how to use – and encourage team members to use – augmented analytics.’.

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Analytics Advertising Cost-Benefit Enterprise 52

DataRobot Blog

JULY 8, 2018

In our previous article, we introduced IBM Watson Studio and discussed helping our CMO and marketing team better utilize limited resources with advanced analytics. by Jen Underwood. In this article, we will reveal. Read More.

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Smart Data Collective

NOVEMBER 12, 2021

Big data has helped companies identify promising cost-saving measures, recruit the best talent, optimize their marketing strategies and realize many other benefits. However, there are a lot of other benefits of big data that have not gotten as much attention. However, the converse approach can also be useful.

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Data-driven Cost-Benefit Data mining Big Data 103

Jedox

JULY 17, 2018

New software technologies empower the office of finance and other lines of business to capture data, share knowledge, and align on common goals to optimize the budgeting and forecasting process and drive performance across the organization. Forbes 2018, 10 Predictions For AI, Big Data, And Analytics in 2018.

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Smarten

AUGUST 23, 2022

THAT is what they want in analytics as well and if you don’t give it to them, they are unlikely to adopt the analytical tools you invested in or to achieve the results you wanted for optimizing resources, improving productivity and, most importantly, engaging in fact-based decision making that will improve the business bottom line.

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Data-driven Sales Optimization Machine Learning 76

Cloudera

SEPTEMBER 12, 2018

It was deeply gratifying to see so many organizations deploying the tools and techniques of data science and advanced analytics to solve difficult and important problems. I predict that next year’s competition will be even more amazing as we continue pushing the frontiers of data science forward.

Machine Learning 46

Machine Learning Big Data Data Science Data Warehouse 46

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. In our world of Big Data, marketers no longer need to simply rely on their gut instincts to make marketing decisions.

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Machine Learning Data Integration Marketing Predictive Modeling 76

Sisense

JULY 29, 2020

That’s where data and analytics are vital: They can help you make the right decisions to shape your organization’s future, both near- and long-term. Using data and analytics to decelerate and treat COVID-19: Luma Health. The COVID-19 pandemic — When pivots must outpace evolution.

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Analytics Digital Transformation Data-driven Sales 95

Birst BI

DECEMBER 18, 2018

Birst Smart Analytics offers a new set of AI-enabled capabilities that leverage machine learning algorithms to generate automated and personalized insights. Business users can tap into the power of data science and instantly understand not just what is happening in their business, but why. How does it work?

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KPI Analytics Machine Learning Dashboards 89

Smarten

MAY 18, 2022

If a sales manager is considering how to optimize her sales team and leverage customer product and purchasing preferences, the business would want to encourage creativity and out-of-the box thinking. Context-searching provides the same kind of support.

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Data-driven Sales Metrics Testing 67