Data Science Blog

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI.

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Data Models Data Modeling Business Intelligence Business Intelligence 245

Pickl AI

JANUARY 15, 2025

Summary: Business Intelligence tools are software applications that help organizations collect, process, analyse, and visualize data from various sources. Introduction Business Intelligence (BI) tools are essential for organizations looking to harness data effectively and make informed decisions.

Business Intelligence 52

Business Intelligence Business Intelligence Power BI Data Visualization 52

The Data Administration Newsletter

JULY 18, 2023

The recently published report by Research Nester, Global Data Mining Tool Market: Global Demand Analysis & Opportunity Outlook 2027, delivers detailed overview of the global data mining tool market in terms of market segmentation by service type, function type, industry type, deployment type, and region.

Data Mining 52

Data Mining Data Mining Data Mining Big Data 52

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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Smart Data Collective

APRIL 1, 2020

Big data is redefining the world of marketing. A growing number of SaaS companies are looking for ways to use big data to get more value from leads and business opportunities. One of the ways businesses can rely more on big data is with SEO. Big Data is Driving More Value to SEO.

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Big Data Big Data Data Mining Data Mining 104

Becoming Human

JANUARY 23, 2023

Just like this in Data Science we have Data Analysis , Business Intelligence , Databases , Machine Learning , Deep Learning , Computer Vision , NLP Models , Data Architecture , Cloud & many things, and the combination of these technologies is called Data Science.

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Data Science Big Data Big Data Deep Learning 105

Data Science Blog

JUNE 21, 2023

Process Mining demands Big Data in 99% of the cases, releasing bad developed extraction jobs will end in big cost chunks down the value stream. Process Mining – Data Extraction The data extraction for process mining should be well planed and match the data strategy of the organization.

Big Data 130

Big Data Big Data Data Engineering Data Engineering 130

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. Working with massive structured and unstructured data sets can turn out to be complicated. The raw data can be fed into a database or data warehouse.

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Database Data Visualization Big Data Big Data 130

ODSC - Open Data Science

FEBRUARY 8, 2023

Big Data here is a fundamental part of the scenario as it enables the technical integration of data from all digital environments along the customer path. BigQuery operation principles Business intelligence projects presume collecting information from different sources into one database.

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Database Data Science Big Data Big Data 97

Data Science Blog

FEBRUARY 4, 2023

The fusion of data in a central platform enables smooth analysis to optimize processes and increase business efficiency in the world of Industry 4.0 using methods from business intelligence , process mining and data science.

Cloud Data 147

Cloud Data Data Science Business Intelligence Business Intelligence 147

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. And you should have experience working with big data platforms such as Hadoop or Apache Spark.

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Dataconomy

JUNE 13, 2023

At its core, decision intelligence involves collecting and integrating relevant data from various sources, such as databases, text documents, and APIs. This data is then analyzed using statistical methods, machine learning algorithms, and data mining techniques to uncover meaningful patterns and relationships.

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Power BI Data Analysis Data Analysis Artificial Intelligence 103

Pickl AI

FEBRUARY 28, 2023

However, Data Scientists use tools like Python, Java, and Machine Learning for manipulating and analysing data. Significantly, in contrast, Data Analysts utilise their proficiency in a relational databases, Business Intelligence programs and statistical software.

Data Analyst 52

Data Analyst Data Scientist Data Science Computer Science 52

IBM Journey to AI blog

JULY 24, 2023

IT operations analytics (ITOA) vs. observability ITOA and observability share a common goal of using IT operations data to track and analyze how a system is performing to improve operational efficiency and effectiveness. It aims to understand what’s happening within a system by studying external data.

Analytics 69

Analytics Analytics Predictive Analytics Big Data 69

IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge.

Machine Learning 68

Machine Learning Machine Learning Data Mining Data Mining 68

Pickl AI

JULY 18, 2023

Its speed and performance make it a favored language for big data analytics, where efficiency and scalability are paramount. SAS: Analytics and Business Intelligence SAS is a leading programming language for analytics and business intelligence. Q: What are the advantages of using Julia in Data Science?

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Data Science SQL Data Scientist Python 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

OCTOBER 14, 2024

This setting often fosters collaboration and networking opportunities that are invaluable in the Data Science field. Specialised Master’s Programs Specialised Master’s programs focus on niche areas within Data Science, such as Artificial Intelligence , Big Data , or Machine Learning.

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Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 23, 2024

Synergy Between Artificial Intelligence and Data Science AI and Data Science complement each other through their unique but interconnected roles in data processing and analysis. Deep Learning: Advanced neural networks drive Deep Learning , allowing AI to process vast amounts of data and recognise complex patterns.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Mlearning.ai

MAY 23, 2023

Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. Data processing does the task of exploring the data, mining it, and analyzing it which can be finally used to generate the summary of the insights extracted from the data.

Data Science 52

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