Data Science, Forecasting and Unstructured Data

Data Science

Forecasting

Unstructured Data

Data science vs data analytics: Unpacking the differences

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

Data Science Data Analytics Prescriptive Analytics Analytics

Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science

Data Science Statistics Business Intelligence Visualization

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Understanding User Needs and Satisfying Them

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Trending Sources

Data science vs. machine learning: What’s the difference?

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

Machine Learning Data Science Statistics Deep Learning

Webinars

The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Understanding User Needs and Satisfying Them

MORE WEBINARS

Face Key-point Recognition Using CNN

Analytics Vidhya

JULY 15, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview of the project: The goal of this project is to forecast. The post Face Key-point Recognition Using CNN appeared first on Analytics Vidhya.

Forecasting

Forecasting Data Science Publishing Analytics

Maximizing Supply Chain Agility through the “Last Mile” Commitment

Cloudera

JANUARY 5, 2021

In today’s retail environment, retailers realize that building demand forecasts simply based upon historical transaction, promo, and pricing data alone is not good enough. Data today has a shelf life much like produce and needs to be updated in real-time to be relevant. Including new data sources like demand signals (e.g.

Forecasting

Forecasting Cost-Benefit Sales Unstructured Data

Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

DECEMBER 19, 2023

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

Machine Learning

Machine Learning Optimization Unstructured Data Sales

Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

SEPTEMBER 23, 2020

The market for data warehouses is booming. One study forecasts that the market will be worth $23.8 While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes.

Data Lake

Data Lake Data Warehouse Unstructured Data Big Data

Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

APRIL 25, 2022

“You can think that the general-purpose version of the Databricks Lakehouse as giving the organization 80% of what it needs to get to the productive use of its data to drive business insights and data science specific to the business.

Recreation/Entertainment

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data

What Are the Industries That Benefit Most from Big Data?

Smart Data Collective

FEBRUARY 2, 2021

In general, Big Data can help businesses in all fields – it’s not something reserved for tech companies. However, some industries have more to benefit from Big Data than others and have reached impressive milestones because data science and data analytics have helped them streamline their operations. Healthcare.

Big Data

Big Data Recreation/Entertainment Cost-Benefit Finance

From Data to Decisions with Actionable Insights

Sisense

JANUARY 22, 2021

Analytics must cope with both structured and unstructured data to achieve optimal results. As we’ll see, very few ML and AI analytics platforms today embody the data science and engineering sophistication to accomplish such a feat with an outcome of actionable insights whose profit justify their cost.

Machine Learning

Machine Learning Unstructured Data Forecasting Advertising

COVID-19 Effects on Financial Services & Managing Risk

bridgei2i

APRIL 23, 2020

Better Forecasting and Optimization. They also have to assess loss forecasting and reserving based on new data sources. By deploying accelerators like Watchtower banks can understand rapidly changing KPIs and anomalies when forecasts are failing. Learn MORE. “and

Risk

Risk Management Scorecard Forecasting

Modernize Using The BI & Analytics Magic Quadrant

Rita Sallam

JULY 22, 2016

Q2: Would you consider Sisense better than others in handling big and unstructured data? Not sure about that, but Sisense is well suited for easily harmonizing, combining and modeling many different, complex and large data sets for fast interactive analysis. Research VP, Business Analytics and Data Science.

Analytics

Analytics Business Intelligence Metadata Statistics

8 Modeling Tools to Build Complex Algorithms

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. Without uncurtailed and unlimited access to modeling tools, data science teams will be handcuffed in their work.

Modeling

Modeling Deep Learning Machine Learning Statistics

7 key Microsoft Azure analytics services (plus one extra)

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Data warehouses are designed for questions you already know you want to ask about your data, again and again. Datamarts in Power BI.

Data Lake

Data Lake Analytics Data Warehouse Machine Learning

Introducing the Next Generation of Text AI for AI Cloud Platform

DataRobot

DECEMBER 16, 2021

While it is easy to accumulate text data, it can be extremely difficult to analyze text due to the ambiguity of human language. It is precisely because of the large volume and complexities of navigating unstructured data that DataRobot has focused on assisting our users to unlock insights from text. More Value with Less Efforts.

Experimentation

Experimentation Unstructured Data Deep Learning Modeling

It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

CIO Business Intelligence

MAY 24, 2022

Unlocking the value of data with in-depth advanced analytics, focusing on providing drill-through business insights. Providing a platform for fact-based and actionable management reporting, algorithmic forecasting and digital dashboarding. Today transactional data is the largest segment, which includes streaming and data flows.

Data-driven

Data-driven Data Lake Data Warehouse Cost-Benefit

Top 10 Analytics And Business Intelligence Buzzwords For 2020

datapine

DECEMBER 4, 2019

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

Business Intelligence

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics

Data Leaders Brief

Data science vs data analytics: Unpacking the differences

Top Data Science Tools That Will Empower Your Data Exploration Processes

Webinars

Trending Sources

Data science vs. machine learning: What’s the difference?

Webinars

Face Key-point Recognition Using CNN

Maximizing Supply Chain Agility through the “Last Mile” Commitment

Anomaly detection in machine learning: Finding outliers for optimization of business functions

Differentiating Between Data Lakes and Data Warehouses

Databricks’ new data lakehouse aims at media, entertainment sector

What Are the Industries That Benefit Most from Big Data?

From Data to Decisions with Actionable Insights

COVID-19 Effects on Financial Services & Managing Risk

Modernize Using The BI & Analytics Magic Quadrant

8 Modeling Tools to Build Complex Algorithms

7 key Microsoft Azure analytics services (plus one extra)

Introducing the Next Generation of Text AI for AI Cloud Platform

It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

Top 10 Analytics And Business Intelligence Buzzwords For 2020

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