CIO Business Intelligence

APRIL 25, 2022

An education in data science can help you land a job as a data analyst , data engineer , data architect , or data scientist. Here are the top 15 data science boot camps to help you launch a career in data science, according to reviews and data collected from Switchup.

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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. 2) Data Discovery/Visualization. We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Data Science 101

JUNE 10, 2019

Getting your first data science job might be challenging, but it’s possible to achieve this goal with the right resources. Before jumping into a data science career , there are a few questions you should be able to answer: How do you break into the profession? What skills do you need to become a data scientist?

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Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

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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. The online program includes an additional nonrefundable technology fee of US$395 per course.

Big Data 126

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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 76

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Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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O'Reilly on Data

DECEMBER 12, 2019

If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. Small residuals usually mean a model is right, and large residuals usually mean a model is wrong. Interpretable ML models and explainable ML.

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CIO Business Intelligence

JUNE 7, 2022

Data analytics and data science are closely related. Data analytics is a component of data science, used to understand what an organization’s data looks like. Generally, the output of data analytics are reports and visualizations. Data analytics vs. data analysis.

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Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. imputation of missing values). ref: [link].

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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

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datapine

DECEMBER 4, 2019

Moreover, as most predictive analytics capabilities available today are in their infancy — they have simply not been used for long enough by enough companies on enough sources of data – so the material to build predictive models on was quite scarce. Last but not least, there is the human factor again.

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Smarten

FEBRUARY 6, 2025

This visual development approach uses a graphical user interface (GUI) to support programmers as they build applications. No-Code solutions utilize visual drag-and-drop interfaces and require no coding, but rather are configured and implemented quickly, using the skilled application of tools and techniques.

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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.

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Machine Learning Data Science Statistics Deep Learning 54

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?”.

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Smarten

MARCH 18, 2019

Data Science and Predictive Analytics Made Simple! Imagine a world where data science and predictive analytics tools are created for business users!

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Juice Analytics

MARCH 11, 2021

However, the data was essentially stored in old copies of the paper magazine, not a format that was conducive to delivering insights to their target audience. (3) People don’t want data, they want solutions. How are you going to turn that data into a solution? She crafts the interface and interactions to make the data intuitive.

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Domino Data Lab

SEPTEMBER 18, 2019

Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Interactive Data Visualization in Python. In this chapter, a data exploration was performed on a public Zillow data set.

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Smart Data Collective

SEPTEMBER 25, 2019

Clearly defining what your career goals are prior to selecting a career focus is a very important first step, since there many different paths you can take within the data science field. The data science industry offers various useful computer languages. Find A Specific Tool To Specialize In.

Big Data 101

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Smarten

NOVEMBER 23, 2023

“These tools enable data literacy and digital transformation and increase team productivity and creativity, encouraging power users and those with average technology skills to dive into analytics ad use fact-based decision-making to improve market positioning.”

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Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Access to Flexible, Intuitive Predictive Modeling. Apply Data Filters. Forecasting. Classification.

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DataRobot

NOVEMBER 1, 2021

Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions.

Machine Learning 98

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Smarten

SEPTEMBER 11, 2017

Read a report, attend a conference and your head is swirling with terms like ‘assisted predictive modeling’, plug n’ play predictive analysis, smart visualization, augmented data discovery and augmented data preparation. Take plug n’ play predictive analytics for example.

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CIO Business Intelligence

MAY 9, 2024

And they should have a proficiency in data science and analytics to effectively leverage data-driven insights and develop AI models. This includes skills in statistical analysis, data visualization, and predictive modeling.

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Smarten

OCTOBER 31, 2022

Embedded BI with integration APIs allows users to leverage single sign-on within familiar software and perform analytics from within that solution.

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Smarten

FEBRUARY 28, 2019

If Data Science was once the sole domain of analysts and data scientists, Augmented Data Science represents the democratized view of this domain. Augmented data science automates and simplifies analysis with machine learning so implementation, training and adoption of these tools is rapid and successful.

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Smarten

AUGUST 21, 2019

These tools allow business users to leverage augmented analytics that provide guides and suggestions to help the business user more quickly and effectively produce clear advanced analytics with little to no training, thereby transforming the average business user into a Citizen Data Scientist.

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Domino Data Lab

AUGUST 12, 2021

For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with. In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase.

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Smarten

JANUARY 17, 2020

As one of its Strategic Assumptions, Gartner predicted that ‘By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’ Look for Self-Serve Data Preparation , Smart Data Visualization , and Assisted Predictive Modeling.

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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?

Machine Learning 73

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Sisense

SEPTEMBER 9, 2019

We were most interested in exploring if it was possible to predict the return rate on a new product based on historical return rates of products with similar features. Then we ran Kraken’s machine learning and predictive modeling engine to get the results. Full circle data experience: achieved. Lessons Learned.

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Smarten

MARCH 5, 2024

The Citizen Data Scientist phenomenon is in full swing and, while the approach has its detractors, the proof is in success, and many organizations are actively succeeding using the Citizen Data Scientist approach.

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Smarten

JULY 26, 2022

Users can share reports and data via WhatsApp, email, chat or other content sharing apps on mobile devices, encouraging information sharing and collaboration. The Smarten mobile application provides intuitive dashboards and reports, stunning visualizations, dynamic charts and graphs and key performance indicators (KPIs).

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Analytics Key Performance Indicator Business Intelligence Dashboards 74

Smarten

OCTOBER 10, 2024

Machine learning has evolved to support the average business user with tools and techniques that make it easier to gather and analyze data using simple techniques that are supported by analytical techniques, without requiring business users to have data science skills.

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CIO Business Intelligence

OCTOBER 13, 2023

Data scientist As companies embrace gen AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate.

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CIO Business Intelligence

MAY 10, 2022

Marketing data-integration CDPs: These CDPs focus on data operations, with powerful data manipulation and governance capabilities, but with non-technical, user-friendly interfaces. Segment is a data-integration CDP designed to collect data and then distribute it in real time to other systems. Treasure Data CDP.

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Smarten

APRIL 25, 2024

Whether you are trying to solve a business problem, get to the heart of that problem, find a business opportunity, predict the need for resources, new products or locations or understanding changes in your customer buying behavior, you don’t have time to learn complex tools or take training in analytics.

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