Knowledge Hut

MAY 1, 2024

A data scientist is a person who is trained and experienced in working with data, i.e. data gathering, data cleaning, data preparation, data transformation, and data analysis. These steps will help understand the data, extract hidden patterns and put forward insights about the data.

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Snowflake

JUNE 6, 2024

Faster, easier AI/ML and data engineering workflows Explore, analyze and visualize data using Python and SQL. Discover valuable business insights through exploratory data analysis. Develop scalable data pipelines and transformations for data engineering.

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SQL Python Machine Learning Data Workflow 95

Knowledge Hut

JANUARY 18, 2024

Both data science and software engineering rely largely on programming skills. However, data scientists are primarily concerned with working with massive datasets. Data Science is strongly influenced by the value of accurate estimates, data analysis results, and understanding of those results.

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Software Engineer Software Engineering Data Science Engineering 97

ProjectPro

FEBRUARY 16, 2023

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

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Monte Carlo

OCTOBER 5, 2023

Enter the world of data clean rooms – the super secure havens where you can mix and mingle data from different sources to get insights without getting your hands dirty with the raw data. How data clean rooms work Data clean rooms combine and analyze different data sources without directly accessing the raw data.

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Knowledge Hut

APRIL 23, 2024

Data Science is the field that focuses on gathering data from multiple sources using different tools and techniques. Whereas, Business Intelligence is the set of technologies and applications that are helpful in drawing meaningful information from raw data. Data Usage It stores the data in a sorted manner for future use.

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Knowledge Hut

DECEMBER 7, 2023

In today's data-driven world, businesses and organizations rely heavily on data to make informed decisions and gain a competitive edge. This has increased the demand for professionals skilled in data analysis and visualization tools. You may wonder if the Power BI Certification Path is worth pursuing or not.

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Knowledge Hut

DECEMBER 26, 2023

Features: Effective Cost Analysis Simple UI and intuitive dashboards Usage Trend and Resource Cost Analytics Gives Recommendations for unused resources, downscaling, relocation, and reallocations 6. Informatica Informatica is a leading industry tool used for extracting, transforming, and cleaning up raw data.

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Ascend.io

NOVEMBER 21, 2023

More importantly, we will contextualize ELT in the current scenario, where data is perpetually in motion, and the boundaries of innovation are constantly being redrawn. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

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Edureka

AUGUST 2, 2023

Programming Languages for Data Scientists Here are the top 11 programming languages for data scientists, listed in no particular order: 1. Due to its strong data analysis and manipulation skills, it has significantly increased its prominence in the field of data science. Embark on Your Data Science Journey Today!

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Knowledge Hut

OCTOBER 27, 2023

In this article, we will be discussing 4 types of d ata Science Projects for resume that can strengthen your skills and enhance your resume: Data Cleaning Exploratory Data Analysis Data Visualization Machine Learning Data Cleaning A   data scientist,   most likely spend nearly 80% of their time cleaning data.

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Meltano

OCTOBER 5, 2022

This involves continually striving to reduce wasted effort, identify gaps and correct them, and improve data development and deployment processes. While definitions of each of these roles may vary across organizations, each is responsible for making data available to data analysts, scientists, and other team members who depend on it.

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Knowledge Hut

NOVEMBER 27, 2023

This is important because this will help you understand what areas to focus on while following the Data Science Learning Path. Is it the part where you turn raw data into useful ones, or it the part where you engineer new features out of the existing ones in order to help create suitable models?

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Knowledge Hut

JANUARY 18, 2024

Data Science initiatives from an operational standpoint help organizations optimize various aspects of their business, such as supply chain management , inventory segregation, and management, demand forecasting, etc. A data analyst would be a professional who will be able to accomplish all the tasks mentioned in the process of data analysis.

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Monte Carlo

MAY 28, 2024

Data Validation : Perform quality checks to ensure the data meets quality and accuracy standards, guaranteeing its reliability for subsequent analysis. Data Storage : Store validated data in a structured format, facilitating easy access for analysis. Used for identifying and cataloging data sources.

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Edureka

SEPTEMBER 23, 2024

They use various tools, techniques, and methodologies borrowed from statistics, mathematics computer science to analyze large amounts of data. Within the context of AI vs Data Science, It is worth defining that although Data science majorly defines itself with data analysis, it is a critical element in creating AI systems.

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Knowledge Hut

APRIL 25, 2024

They simplify data processing for our brains and give readers a quick overview of past, present, and future performance by helping the user to visualize otherwise complex and weighty raw data. PepsiCo also used the BI's capacity to cut down analysis time by up to 90%. Data from diverse sources must be mixed.

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U-Next

MARCH 7, 2023

Taking data from sources and storing or processing it is known as data extraction. Define Data Wrangling The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed.

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Data Mining Scala Government Data Governance 96

Knowledge Hut

FEBRUARY 7, 2023

Data analysis, statistical models, and other quantitative techniques are used in business analytics (BA), a collection of disciplines and technology. It entails a rigorous, iterative examination of the data within an organization with a focus on statistical analysis to inform decision-making.

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Knowledge Hut

SEPTEMBER 27, 2023

Discuss projects you've undertaken, challenges you've overcome, and the impact of your work on data analysis and decision-making processes. Emphasize your data analysis and visualization skills, showcasing your ability to transform complex data sets into actionable insights.

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Knowledge Hut

JULY 4, 2023

Data analysis and Interpretation: It helps in analyzing large and complex datasets by extracting meaningful patterns and structures. By identifying and understanding patterns within the data, valuable insights can be gained, leading to better decision-making, and understanding of underlying relationships.

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Knowledge Hut

JULY 21, 2023

Data visualization charts are an invaluable tool in simplifying data analysis and presenting insights in visually appealing ways. Data visualization charts are graphical representations of data that help organizations understand and interpret complex information.

Raw Data 52

Raw Data BI Data Data Analysis 52

Knowledge Hut

JANUARY 11, 2024

For example, a retail store generates data regularly related to purchases. Now, they turn these raw data units into a fruitful chunk of information based on which they plan their future marketing strategies. Any department wanting to access any data unit would only have to give the command and get the required information.

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Knowledge Hut

FEBRUARY 15, 2023

Not very surprisingly, the amount of data used and shared between networks is infinite. This has led to data analysis being a vital element of most businesses. Data analysts are professionals who manage and analyze data that give insight into business goals and help align them. What is Data Analysis?

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Knowledge Hut

APRIL 25, 2024

Contrarily, Data Wrangling is done during iterative analysis and model construction. Data exploration The initial phase in data analysis is called data exploration, and it involves looking at and visualizing data to find insights right away or point out regions or patterns that need further investigation.

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Big Data Data Analytics Manufacturing Retail 52

Edureka

JULY 18, 2024

Therefore, businesses analysts with strong coding skills can automate repetitive tasks, build custom data pipelines, and integrate disparate systems seamlessly. Having a sound knowledge of R, SQL, Python, VBA, and Machine Learning enables you to transform raw data into clear, impactful stories for stakeholders.

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Business Analyst BI Raw Data Finance 40

Edureka

SEPTEMBER 11, 2023

Business Intelligence (BI) is a set of technologies, software applications, and methods that help organizations collect, store, analyze, and make sense of large amounts of raw data to get insights that can be used to make decisions. The main goal of BI systems is to make it easier for businesses to make decisions based on data.

Business Intelligence 52

Business Intelligence BI Database-centric Raw Data 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

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ETL Tools Database-centric Data Mining Raw Data 52

Knowledge Hut

OCTOBER 30, 2023

The role of a Power BI developer is extremely imperative as a data professional who uses raw data and transforms it into invaluable business insights and reports using Microsoft’s Power BI. Data Analysis: Perform basic data analysis and calculations using DAX functions under the guidance of senior team members.

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BI Business Intelligence Data Cleanse Business Analyst 52

ProjectPro

FEBRUARY 16, 2023

ETL Architecture on AWS: Examining the Scalable Architecture for Data Transformation ETL Architecture on AWS typically consists of three components - Source Data Store A Data Transformation Layer Target Data Store Source Data Store The source data store is where raw data is stored before being transformed and loaded into the target data store.

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U-Next

FEBRUARY 27, 2023

Introduction Data visualization is critical in this digital age. Tableau Software has seen extensive usage in making businesses more data-driven. A premier tool for data analysis and business intelligence, Tableau is used to visualize business data.

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Knowledge Hut

APRIL 23, 2024

Their operations require collaborations with different team members fulfilling front-end and back-end requirements, including data analysis. Data Engineer Data engineers develop or strategize software to retrieve, sort, and process raw data to extract meaningful information to assess an operation.

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AltexSoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Raw data store section.

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Striim

SEPTEMBER 11, 2024

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

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Knowledge Hut

NOVEMBER 27, 2023

Before being ready for processing, data goes through pre-processing which is a necessary group of operations that translate raw data into a more understandable format and thus, useful for further processing. Common processes are: Collect raw data and store it on a server.

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Databand.ai

JUNE 8, 2023

Key components of an observability pipeline include: Data collection: Acquiring relevant information from various stages of your data pipelines using monitoring agents or instrumentation libraries. Data storage: Keeping collected metrics and logs in a scalable database or time-series platform.

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Snowflake

MARCH 13, 2023

Architecture designed to empower more clients Gem’s cybersecurity platform starts with raw data ingestion from its clients’ cloud environments. Gem uses the fully-managed Snowpipe service, allowing it to stream and process source data in near-real time.

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