Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. The integration of these technologies helps companies harness data for growth and efficiency.

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Data Science Azure Power BI Business Intelligence 246

Smart Data Collective

JULY 9, 2019

Currently, companies can review thousands of data points on individual customers for enhanced comprehension of their best customers. One example is the use of big data to differentiate millennial buying habits from older customers. Otherwise, your business may be sacrificing new opportunities. Leverage Your Big Data.

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Big Data Big Data Analytics Analytics 111

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. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245

Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

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.

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Business Intelligence Business Intelligence Power BI Data Visualization 52

The Data Administration Newsletter

APRIL 20, 2021

Enter predictive analytics, and […]. It’s usually somewhat tedious for all parties involved, until a safety issue actually arises. At this point, all the old procedures will be given a good once-over.

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Predictive Analytics Analytics Analytics Big Data 59

Pickl AI

JANUARY 28, 2025

Summary: Understanding Business Intelligence Architecture is essential for organizations seeking to harness data effectively. This framework includes components like data sources, integration, storage, analysis, visualization, and information delivery. What is Business Intelligence Architecture?

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Business Intelligence Business Intelligence ETL Data Lakes 52

Smart Data Collective

AUGUST 10, 2021

Big data and analytics technology is rapidly changing the future of modern business. Over 67% of companies spend over $10,000 a year on analytics solutions. Investments in analytics are being made across all major industries. Analytics Becomes Major Asset to Companies Across All Sectors.

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Analytics Analytics Big Data Big Data 137

Data Science Dojo

SEPTEMBER 5, 2024

The field of data science emerged in the early 2000s, driven by the exponential increase in data generation and advancements in data storage technologies. Data science plays a crucial role in numerous applications across different sectors: Business Forecasting : Helps businesses predict market trends and consumer behavior.

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Computer Science Computer Science Data Science Machine Learning 195

Data Science Dojo

SEPTEMBER 5, 2024

The field of data science emerged in the early 2000s, driven by the exponential increase in data generation and advancements in data storage technologies. Data science plays a crucial role in numerous applications across different sectors: Business Forecasting : Helps businesses predict market trends and consumer behavior.

Computer Science 195

Computer Science Computer Science Data Science Machine Learning 195

Pickl AI

DECEMBER 2, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

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Big Data Big Data Data Lakes Apache Hadoop 52

Smart Data Collective

MAY 20, 2019

We’re well past the point of realization that big data and advanced analytics solutions are valuable — just about everyone knows this by now. Big data alone has become a modern staple of nearly every industry from retail to manufacturing, and for good reason. Basic Business Intelligence Experience is a Must.

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Analytics Analytics Data Analyst Machine Learning 111

Smart Data Collective

JUNE 11, 2025

Reading: Monitoring Data Without Turning into Big Brother Share Notification Font Resizer Aa Font Resizer Aa Search About Help Privacy Follow US © 2008-23 SmartData Collective. Alex Blackwell 10 Min Read AI-Generated Image from Google Labs SHARE Data monitoring is no longer optional for large-scale digital systems.

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Dataconomy

MAY 16, 2025

Importance of advanced analytics In today’s data-driven world, the ability to interpret vast quantities of information is vital for success. Advanced analytics equips organizations with tools to tackle intricate business challenges that standard business intelligence (BI) tools may not effectively address.

Analytics 91

Analytics Analytics Big Data Analytics Big Data Analytics 91

Smart Data Collective

AUGUST 15, 2019

According to data published by the Work Institute , employers will pay an estimated $680 billion in turnover costs by 2020. However, 77% of those turnovers could be prevented using big data. According to a study conducted by the Dryden Group, cutting indirect expenses could save your business 25% in overall expenses.

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Big Data Big Data Predictive Analytics Artificial Intelligence 106

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.

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Cloud Data Data Science Business Intelligence Business Intelligence 147

Smart Data Collective

JUNE 8, 2023

We have talked extensively about the many industries that have been impacted by big data. many of our articles have centered around the role that data analytics and artificial intelligence has played in the financial sector. However, many other industries have also been affected by advances in big data technology.

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Analytics Analytics Data Analysis Data Analysis 105

How to Learn Machine Learning

APRIL 26, 2025

Data Storage and Management Once data have been collected from the sources, they must be secured and made accessible. The responsibilities of this phase can be handled with traditional databases (MySQL, PostgreSQL), cloud storage (AWS S3, Google Cloud Storage), and big data frameworks (Hadoop, Apache Spark).

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Data Science Data Analyst Data Scientist Machine Learning 52

Smart Data Collective

JUNE 16, 2022

Predictive analytics have an unquestionable influence on drawing patterns around consumer behavior and their likelihood to either re-subscribe or discontinue the service. Extract Value From Customer.

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Analytics Analytics Predictive Analytics Big Data 135

Dataconomy

FEBRUARY 6, 2024

This popularity is primarily due to the spread of big data and advancements in algorithms. Data analytics and business intelligence As businesses have opted for digital transformation, they are faced with a tsunami of data that is now incredibly valuable but is burdensome to collect, analyze, and process.

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ML ML Machine Learning Machine Learning 121

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.

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Data Science Analytics Analytics Data Scientist 94

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

Pickl AI

JULY 29, 2024

It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data. In a Hadoop cluster, data stored in the Hadoop Distributed File System (HDFS), which spreads the data across the nodes.

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Hadoop Clustering Big Data Big Data 52

Pickl AI

JUNE 29, 2023

It initiates the collection, indexing, and analysis of machine-generated data in real-time. The tool is loaded with features, thus making it a popular choice for businesses. It helps harness the power of big data and turn it into actionable intelligence. Wrapping it up !!!

Big Data Analytics 52

Big Data Analytics Big Data Analytics Big Data Big Data 52

Pickl AI

OCTOBER 10, 2024

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. This makes drawing actionable insights, spotting patterns, and making data-driven decisions easier.

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Data Quality AWS Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 11, 2023

Data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics that enable faster decision making and insights.

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Data Warehouse Database Cloud Data Big Data 60

Dataconomy

JUNE 13, 2023

By analyzing market trends, customer behavior, and competitor activities, businesses can make well-informed choices that align with their growth goals and capitalize on market opportunities. From zero to BI hero: Launching your business intelligence career Optimal resource allocation is another key aspect of decision intelligence.

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Power BI Data Analysis Data Analysis Artificial Intelligence 103

Pickl AI

NOVEMBER 18, 2024

Selecting the right alternative ensures efficient data-driven decision-making and aligns with your organisation’s goals and budget. Introduction Power BI has become one of the most popular business intelligence (BI) tools, offering powerful Data Visualisation, reporting, and decision-making features. billion to USD 54.27

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Power BI Tableau Data Analysis Data Analysis 52

Pickl AI

MARCH 10, 2025

Summary: Power BI is a business intelligence tool that transforms raw data into actionable insights. Introduction Managing business and its key verticals can be challenging. However, with the surge of data tools like Power BI, you can not only manage the data, but at the same time draw actionable insights from it.

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Power BI Business Intelligence Business Intelligence Analytics 52

Pickl AI

APRIL 2, 2024

There are three main types, each serving a distinct purpose: Descriptive Analytics (Business Intelligence): This focuses on understanding what happened. Think of it as summarizing past data to answer questions like “Which products are selling best?” ” or “What are our customer demographics?”

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Data Science Machine Learning Machine Learning Predictive Analytics 52

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry?

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Analytics Analytics Data Silos Big Data 52

Pickl AI

FEBRUARY 19, 2025

Artificial Intelligence (AI): Enables machines to perform tasks that require human intelligence, such as recognising speech, translating languages, or driving autonomous cars. Big Data: Refers to vast sets of data that traditional tools cannot process; commonly used in industries like social media, e-commerce, and healthcare.

Data Science 52

Data Science Analytics Analytics Machine Learning 52

Pickl AI

JANUARY 16, 2024

Statistical Analysis Firm grasp of statistical methods for accurate data interpretation. Programming Languages Competency in languages like Python and R for data manipulation. Machine Learning Understanding the fundamentals to leverage predictive analytics. Value in 2022 – $271.83 billion In 2023 – $307.52

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Data Analyst Data Analysis Data Analysis Analytics 52

Pickl AI

JUNE 12, 2023

Tableau further has its own drawbacks in case of its use in Data Science considering it is a Data Analysis tool rather than a tool for Data Science. How Professionals Can Use Tableau for Data Science? Professionals can connect to various data sources, including databases, spreadsheets, and big data platforms.

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Tableau Data Science Data Scientist Data Analysis 52

Pickl AI

OCTOBER 16, 2024

It’s popular in corporate environments for Data Analysis and Business Intelligence. Evolving Role of RDBMS in Big Data and Analytics As big data continues to grow, the role of RDBMS is evolving. SQL Server : Developed by Microsoft, SQL Server integrates seamlessly with other Microsoft products.

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Database SQL Analytics Analytics 52

Smart Data Collective

NOVEMBER 21, 2019

Big data is transforming the daily realities of running a business. Companies can use big data to handle certain tasks more quickly and cost-effectively than ever. Vince Campisi, CIO of GE Software, Ash Gupta, an executive with American Express, and many other companies use big data to get a competitive advantage.

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