Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere is not just for data managers.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

IBM Big Data Hub

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. How MLOps will be used within the organization.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

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.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Smart Data Collective

APRIL 5, 2022

The data science profession has become highly complex in recent years. Data science companies are taking new initiatives to streamline many of their core functions and minimize some of the more common issues that they face. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

Cost-Benefit 122

Cost-Benefit Machine Learning Data Science Unstructured Data 122

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 127

Analytics Data Science Unstructured Data Data mining 127

CIO Business Intelligence

JANUARY 17, 2024

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. We rely on cloud-scale technologies and proprietary data science and analytics engines built on open standards to handle massive data sets,” says Mohammed.

Digital Transformation 106

Digital Transformation Dashboards Reporting Data Science 106

AWS Big Data

MARCH 26, 2024

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. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

FineReport

MARCH 24, 2024

Data Analyst Job Description: Major Tasks and Duties Data analysts collaborate with management to prioritize information needs, collect and interpret business-critical data, and report findings. Proficiency in programming languages such as R and SAS is essential for data gathering, cleaning, and visualization.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

JANUARY 20, 2023

But the benefits of BI extend beyond business decision-making, according to data visualization vendor Tableau , including the following: Data-driven business decisions: The ability to drive business decisions with data is the central benefit of BI.

Business Intelligence 135

Business Intelligence Dashboards Data mining OLAP 135

datapine

AUGUST 29, 2022

Best for : the new intern who has no idea what data science even means. An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer vs. data architect.

Analytics 115

Analytics Data Science Statistics Unstructured Data 115

datapine

APRIL 16, 2019

But today, the development and democratization of business intelligence software empowers users without deep-rooted technical expertise to analyze as well as extract insights from their data. Data driven business decisions make or break companies. This is a testament to the importance of online data visualization in decision making.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

datapine

OCTOBER 14, 2020

Visualizing the data and interacting on a single screen is no longer a luxury but a business necessity. They enable you to easily visualize your data, filter on-demand, and slice and dice your data to dig deeper. Maps are important data visualizations and at datapine, we love utilizing them in our dashboards.

Dashboards 235

Dashboards Interactive Reporting KPI 235

datapine

APRIL 11, 2019

In the contemporary world of business, the age-old art of storytelling is far from forgotten: rather than speeches on the Senate floor, businesses rely on striking data visualizations to convey information, drive engagement, and persuade audiences. . Big data commands big stories. Start with data visualization.

Dashboards 169

Dashboards Visualization Data-driven Key Performance Indicator 169

Rocket-Powered Data Science

SEPTEMBER 18, 2018

For the modern digital organization, the proof of any inference (that drives decisions) should be in the data! Rich and diverse data collections enable more accurate and trustworthy conclusions. Higher variety data means that we are adding data from other sensors, other signals, other sources, and of different types.

Big Data 103

Big Data Data Science Measurement Data Collection 103

Domino Data Lab

JANUARY 21, 2021

This blog explores the challenges associated with doing such work manually, discusses the benefits of using Pandas Profiling software to automate and standardize the process, and touches on the limitations of such tools in their ability to completely subsume the core tasks required of data science professionals and statistical researchers.

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

Sisense

APRIL 10, 2020

One of the most-asked questions from aspiring data scientists is: “What is the best language for data science? People looking into data science languages are usually confused about which language they should learn first: R or Python. NLP can be used on written text or speech data. R or Python?”.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Data Science 101

NOVEMBER 8, 2023

What type of data science work did you do? I was definitely more in the analytics space than I ever was the data science space specifically. I did mine through UCSD Extension. 6 months, 240 in-class hours plus god only knows how many hours at home. And why did you choose to transition to product management?

Data Science 59

Data Science Visualization Management Data Processing 59

Cloudera

APRIL 9, 2021

The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. Data Collection – streaming data.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. ML model interpretability and data visualization. – back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Rocket-Powered Data Science

JULY 7, 2019

Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). A reference to a new phase in the Industrial Revolution that focuses heavily on interconnectivity, automation, Machine Learning, and real-time data. They cannot process language inputs generally.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

CIO Business Intelligence

NOVEMBER 28, 2023

By identifying and categorizing named entities, NER empowers data analysts and system engineers to unlock valuable insights from the vast data collected,” Minarik says. Ensure value with visualizations. The process of making unstructured data usable doesn’t end with analysis, Minarik says.

Unstructured Data 116

Unstructured Data Data-driven Visualization Data Quality 116

CIO Business Intelligence

SEPTEMBER 22, 2023

Others aim simply to manage the collection and integration of data, leaving the analysis and presentation work to other tools that specialize in data science and statistics. DMP vs. CDP Lately a cousin of DMP has evolved, called the customer data platform (CDP).

Management 96

Management Advertising Data Lake Sales 96

datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. 6) Smart and faster reporting. click to enlarge**.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataRobot

OCTOBER 20, 2021

What Is Data Literacy? Data literacy is the ability to understand data science and AI applications critically using basic data visualization, communication, and reasoning skills. And beyond uniting diverse stakeholders, data literacy also empowers sectoral regulators to provide industry-specific guidance.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. Free Download. From FineBI.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

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 Collection. Deployment.

Data mining 77

Data mining KDD Data Science Forecasting 77

CIO Business Intelligence

NOVEMBER 22, 2022

From a data strategy perspective, the biggest trend is the need for IT teams to get clear visualization and insight in their applications irrespective of domain, whether on-premises, in the cloud or hybrid environments.” Data collection and management shouldn’t be classified as just another project, Gusher notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

FEBRUARY 6, 2023

One issue is that small businesses rarely have enough resources to set up a dedicated data science (DS) team, nor can they afford to bring in temporary consultants,” said Itzik Levy , CEO of small business management software vcita. They can then use this data to measure the company’s sales performance and predict future outcomes.

Business Intelligence 60

Business Intelligence Forecasting Marketing Sales 60

Alation

JANUARY 17, 2023

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. Better Data Culture. Good data warehouses should be reliable.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

CIO Business Intelligence

JUNE 9, 2022

Others aim simply to manage the collection and integration of data, leaving the analysis and presentation work to other tools that specialize in data science and statistics. Lately a cousin of DMP has evolved, called the customer data platform (CDP). Adobe Audience Manager. OnAudience.

Management 136

Management Advertising Data Lake Sales 136

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. For example, streaming data from sensors to an analytics platform where it is processed and visualized immediately.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Data Science 101

NOVEMBER 1, 2023

And then the software: we made Windows, Linux, Mac, and iPadOS apps Our software helped researchers create eye-tracking projects, record video of the eye movements and from the user’s perspective, and then analyze and clean all that collected data, then apply visualizations, and export everything for further research.

Software 59

Software Testing Visualization Marketing 59

Domino Data Lab

AUGUST 1, 2021

Skater provides a wide range of algorithms that can be used for visual interpretation (e.g. Partial Dependence Plot is another visual method, which is model agnostic and can be successfully used to gain insights into the inner workings of a black-box model like a deep ANN. layer-wise relevance propagation), model distillation (e.g.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Jet Global

AUGUST 14, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. This also helps business functions avoid unnecessary data logjams and giving them instant access they need to the data they so desperately require.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70