IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Pickl AI

DECEMBER 14, 2023

From predicting patient outcomes to optimizing inventory management, these techniques empower decision-makers to navigate data landscapes confidently, fostering informed and strategic decision-making. It is a mathematical framework that aims to capture the underlying patterns, trends, and structures present in the data.

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Tableau

JANUARY 25, 2024

Kristin Adderson January 25, 2024 - 11:21pm Harveen Kathuria Senior Director, Product Management Tableau has been on the journey to help people see and understand their data for over two decades. Thanks to data analysts, this mission has been a success and will continue to be a success.

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Dataconomy

SEPTEMBER 16, 2024

It was designed to retrieve and manage data stored in relational databases. This versatile programming language is widely used by database administrators, developers, and data analysts. Whether you’re working with MySQL, SQL Server, or another DBMS, mastering this language allows seamless data manipulation and retrieval.

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Pickl AI

FEBRUARY 19, 2025

Think of Data Science as the overarching umbrella, covering a wide range of tasks performed to find patterns in large datasets, while Data Analytics is a task that resides under the Data Science umbrella to query, interpret, and visualize datasets. The main goal of Data Analytics is to improve decision-making.

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Pickl AI

JULY 23, 2023

Using the right data analytics techniques can help in extracting meaningful insight, and using the same to formulate strategies. The analytics techniques like descriptive analytics, predictive analytics, diagnostic analytics and others find application in diverse industries, including retail, healthcare, finance, and marketing.

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Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Key Components of Data Intelligence In Data Intelligence, understanding its core components is like deciphering the secret language of information.

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Pickl AI

JUNE 25, 2023

This knowledge enables them to make data-backed decisions to address challenges and capitalize on opportunities. Predictive Analytics Predictive analytics involves the use of historical data, statistical algorithms, and machine learning techniques to forecast future outcomes or trends.

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Pickl AI

JUNE 4, 2024

By establishing a well-defined data collection and management strategy, organizations in the sustainable energy sector can harness the power of data to optimize energy production and consumption, drive efficiency improvements, and ultimately contribute to a cleaner energy future.

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Pickl AI

OCTOBER 17, 2024

Summary: Descriptive Analytics tools transform historical data into visual reports, helping businesses identify trends and improve decision-making. Popular tools like Power BI, Tableau, and Google Data Studio offer unique features for Data Analysis. What is Descriptive Analytics?

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Pickl AI

OCTOBER 18, 2023

Player Recruitment and Draft Analytics Evaluating potential draft picks or player acquisitions by analyzing their performance data and comparing it to team needs. Game Simulation and Predictive Analytics Using predictive models to forecast game outcomes, player performance, and even fantasy sports outcomes.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis.

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Pickl AI

JANUARY 29, 2024

ML focuses on enabling computers to learn from data and improve performance over time without explicit programming. Key Components In Data Science, key components include data cleaning, Exploratory Data Analysis, and model building using statistical techniques. billion in 2022 to a remarkable USD 484.17

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Pickl AI

FEBRUARY 21, 2023

Understanding the appropriate ways to use data remains critical to success in finance, education and commerce. Accordingly, data collection from numerous sources is essential before data analysis and interpretation. Data mining can be applied to many data types, including customer, financial, medical, and scientific data.

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Pickl AI

JANUARY 9, 2025

Summary: Operations Analyst job in 2025 are integral to improving efficiency, data analysis, and process optimisation. With career growth opportunities and a focus on data-driven decisions, this job remains central to organisational success. What Skills are Essential for an Operations Analyst Job in 2025?

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Pickl AI

JUNE 12, 2023

How Professionals Can Use Tableau for Data Science? Tableau is a powerful data visualization and business intelligence tool that can be effectively used by professionals in the field of data science. This helps in understanding the underlying patterns, trends, and relationships within the data.

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Pickl AI

SEPTEMBER 24, 2024

Read More: Use of AI and Big Data Analytics to Manage Pandemics Overview of Uber’s Data Analytics Strategy Uber’s Data Analytics strategy is multifaceted, focusing on real-time data collection, predictive analytics, and Machine Learning.

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Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems.

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Pickl AI

JULY 3, 2023

Here are steps you can follow to pursue a career as a BI Developer: Acquire a solid foundation in data and analytics: Start by building a strong understanding of data concepts, relational databases, SQL (Structured Query Language), and data modeling. Is BI developer same as data analyst?

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Pickl AI

OCTOBER 18, 2023

Data serves as the backbone of informed decision-making, and the accuracy, consistency, and reliability of data directly impact an organization’s operations, strategy, and overall performance. Informed Decision-making High-quality data empowers organizations to make informed decisions with confidence.

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Pickl AI

JULY 2, 2023

Spark’s in-memory processing capability enables high-speed data processing, making it suitable for real-time and batch-processing workloads. Scalability and Performance It also provides a cloud-based infrastructure that can handle large volumes of data. This saves time and increases performance.

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Pickl AI

FEBRUARY 4, 2024

Alteryx’s Capabilities Data Blending: Effortlessly combine data from multiple sources. Predictive Analytics: Leverage machine learning algorithms for accurate predictions. This makes Alteryx an indispensable tool for businesses aiming to glean insights and steer their decisions based on robust data.

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Pickl AI

DECEMBER 6, 2024

Future Trends in Data Analytics and SEO for Rehab Centres As technology evolves, so too will the role of Data Analytics in shaping SEO strategies for rehab centres. One emerging trend is the integration of Artificial Intelligence (AI) into Data Analysis processes.

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Pickl AI

NOVEMBER 2, 2023

A cheat sheet for Data Scientists is a concise reference guide, summarizing key concepts, formulas, and best practices in Data Analysis, statistics, and Machine Learning. It serves as a handy quick-reference tool to assist data professionals in their work, aiding in data interpretation, modeling , and decision-making processes.

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Pickl AI

JANUARY 31, 2024

Impactful Decision-Making Data Scientists play a crucial role in helping organizations make informed decisions based on data analysis. Innovation and Problem-Solving Data Science involves addressing complex problems and finding innovative solutions. Lakhs per year Data Science Engineer ₹9.50

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phData

SEPTEMBER 4, 2024

Leveraging on ThoughtSpot’s built-in usage-based ranking ML algorithm, SpotIQ improves with each use, making data analysis more intuitive and proactive for users. Full Stack Service ThoughtSpot Mode gives data teams everything they need to go from the back end to the front end. Why Use ThoughtSpot?

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Pickl AI

DECEMBER 10, 2024

Key Takeaways Exalytics, Exalogic, and Exadata provide optimised analytics, middleware, and database solutions. Exalytics delivers lightning-fast data analysis and visualisation capabilities. Exadata accelerates query execution and optimises storage for large-scale data management.

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Pickl AI

DECEMBER 16, 2024

The objective is to guide businesses, Data Analysts, and decision-makers in choosing the right tool for their needs. Whether you aim for comprehensive data integration or impactful visual insights, this comparison will clarify the best fit for your goals.

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Alation

MARCH 21, 2023

The travel and tourism industry can use predictive, descriptive, and prescriptive analytics to make data-driven decisions that ultimately enhance revenue, mitigate risk, and increase efficiencies. Using Alation, ARC automated the data curation and cataloging process. “So

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phData

JULY 25, 2023

Some examples include extracting most of your data, which includes both structured and unstructured data. Your data could already be present in a processed format which would help the Data Analyst spend less time cleaning and preparing the data. What Should My Data Strategy Look Like?

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phData

JULY 25, 2023

Some examples include extracting most of your data, which includes both structured and unstructured data. Your data could already be present in a processed format which would help the Data Analyst spend less time cleaning and preparing the data. What Should My Data Strategy Look Like?

Data Engineering 52

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Pickl AI

JULY 20, 2023

It involves deeper analysis and investigation to identify the root causes of problems or successes. Root cause analysis is a typical diagnostic analytics task. 3. Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes.

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IBM Journey to AI blog

JUNE 5, 2024

Using comprehensive, AI-driven SaaS analytics, businesses can make data-driven decisions about feature enhancements, UI/UX improvements and marketing strategies to maximize user engagement and meet—or exceed—business goals. They may also struggle to fully leverage the predictive capabilities of app analytics.

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Pickl AI

DECEMBER 4, 2024

A key aspect of this evolution is the increased adoption of cloud computing, which allows businesses to store and process vast amounts of data efficiently. According to recent statistics, 56% of healthcare organisations have adopted predictive analytics to improve patient outcomes.

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Dataconomy

MAY 6, 2024

Users need not go through the tedious tasks of manually sorting data, aggregating and processing the sorted data into insights, and churning out analyses and recommendations for sensible decision-making. It can analyze reports or surveys, detect data trends and patterns, undertake scenario breakdowns, and conduct predictive analytics.

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Dataconomy

MARCH 28, 2025

Autoregressive models are fascinating tools in the realm of predictive analytics, frequently used to forecast future values based on historical trends. They leverage patterns found in past data to make informed predictions, which can be extremely valuable in numerous fields, from finance to machine learning.

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Pickl AI

DECEMBER 2, 2024

One powerful combination is the integration of TabPy (Tableau Python Server) with Tableau , a leading data visualisation tool. This integration allows users to leverage Python’s advanced analytical capabilities directly within Tableau, enabling more sophisticated data processing and predictive analytics.

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