Ascend.io

OCTOBER 28, 2024

What is Data Transformation? Data transformation is the process of converting raw data into a usable format to generate insights. It involves cleaning, normalizing, validating, and enriching data, ensuring that it is consistent and ready for analysis.

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Knowledge Hut

DECEMBER 7, 2023

Welcome to the comprehensive guide for beginners on harnessing the power of Microsoft's remarkable data visualization tool - Power BI. In today's data-driven world, the ability to transform raw data into meaningful insights is paramount, and Power BI empowers users to achieve just that. What is Power BI?

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BI Raw Data Datasets Business Intelligence 52

Precisely

SEPTEMBER 19, 2024

It’s important to note that in the AI age, your data governance practices must evolve ensure the ethical use, privacy, and compliance of these technologies. Let’s examine these measures more closely: Data privacy: Implement strict access control policies and mask personally identifiable information (PII) data to protect sensitive information.

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Christophe Blefari

APRIL 21, 2023

Access — you will be able to namespace models with groups and visibility. Data Engineering at Adyen — "Data engineers at Adyen are responsible for creating high-quality, scalable, reusable and insightful datasets out of large volumes of raw data" This is a good definition of one of the possible responsibilities of DE.

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Precisely

DECEMBER 13, 2023

Digital marketing is ideally suited for precise targeting and rapid feedback, provided that business users have access to the detailed demographic and geospatial data they need. These datasets offer information for over 140 countries and territories worldwide, and empower businesses to conduct their analysis at scale.

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Precisely

NOVEMBER 20, 2023

Imagine accessing more detail based on each customer’s home address. You need reference data sets from trusted, authoritative sources like Precisely to do that. Enrichment: The Secret to Supercharged AI You’re not just improving accuracy by augmenting your datasets with additional information.

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Raw Data Insurance Data Portfolio 121

Monte Carlo

JULY 25, 2023

Data curation is the process of transforming and enriching larger amounts of raw data into smaller, more widely accessible subsets of data that provide additional value to the organization or the intended use case. In This Article: What is data curation? Medallion architecture.

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Towards Data Science

NOVEMBER 16, 2023

Unlike streaming data, which needs instant processing, batch data can be processed at scheduled intervals or when resources become available. Splittable in chunks : instead of processing an entire dataset in a single, resource-intensive operation, batch data can be divided into smaller, more manageable segments.

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Monte Carlo

JULY 30, 2024

Data teams can use uniqueness tests to measure their data uniqueness. Uniqueness tests enable data teams to programmatically identify duplicate records to clean and normalize raw data before entering the production warehouse.

Data Validation 52

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Striim

SEPTEMBER 11, 2024

Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures. Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making.

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Databand.ai

JULY 6, 2023

7 Data Pipeline Examples: ETL, Data Science, eCommerce, and More Joseph Arnold July 6, 2023 What Are Data Pipelines? Data pipelines are a series of data processing steps that enable the flow and transformation of raw data into valuable insights for businesses.

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Knowledge Hut

JULY 28, 2023

Data Labeling is the process of assigning meaningful tags or annotations to raw data, typically in the form of text, images, audio, or video. These labels provide context and meaning to the data, enabling machine learning algorithms to learn and make predictions. What is Data Labeling for Machine Learning?

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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

SEPTEMBER 26, 2023

The insights derived from the data in hand are then turned into impressive business intelligence visuals such as graphs or charts for the executive management to make strategic decisions. In this post, we will discuss the top power BI developer skills required to access Microsoft’s power business intelligence software.

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Knowledge Hut

DECEMBER 22, 2023

Linear Algebra Linear Algebra is a mathematical subject that is very useful in data science and machine learning. A dataset is frequently represented as a matrix. Statistics Statistics are at the heart of complex machine learning algorithms in data science, identifying and converting data patterns into actionable evidence.

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Knowledge Hut

JANUARY 29, 2024

In today's data-driven world, where information reigns supreme, businesses rely on data to guide their decisions and strategies. However, the sheer volume and complexity of raw data from various sources can often resemble a chaotic jigsaw puzzle.

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Databand.ai

AUGUST 30, 2023

Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. There are several types of data testing tools.

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The Modern Data Company

APRIL 15, 2024

It offers high-quality, well-managed data streams from every corner of your company, offering clear insights to your tech teams and, critically, your business leaders—your CMOs, CFOs, and CSOs. A Closer Look The biggest draw of data products for business stakeholders is that they enable Transparent Metric Trees.

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Raw Data Government Data Datasets 52

U-Next

MARCH 7, 2023

Most Data Analysts do not require a deep understanding of complex mathematics, even though they should have a foundational knowledge of statistics and mathematics. Statistics, linear algebra, and calculus are generally required for Data Analysts. Why is MS Access important in Data Analytics? What is data extraction?

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Data Mining Scala Government Data Governance 96

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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Striim

AUGUST 7, 2024

Leveraging both platforms’ strengths, companies can achieve higher operational intelligence and security, making real-time anomaly detection more effective and accessible than before. This integration enhances the detection of irregular patterns and potential threats, ensuring rapid response and mitigation.

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DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data. The Data Warehouse(s) facilitates data ingestion and enables easy access for end-users.

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dbt Developer Hub

SEPTEMBER 28, 2022

So let’s say that you have a business question, you have the raw data in your data warehouse , and you’ve got dbt up and running. You’re in the perfect position to get this curated dataset completed quickly! You’ve got three steps that stand between you and your finished curated dataset. Or are you?

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Knowledge Hut

JANUARY 19, 2024

Embracing data science isn't just about understanding numbers; it's about wielding the power to make impactful decisions. Imagine having the ability to extract meaningful insights from diverse datasets, being the architect of informed strategies that drive business success. That's the promise of a career in data science.

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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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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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Raw Data Data Warehouse Data Cleanse Data Integration 52

Towards Data Science

MARCH 9, 2023

Code implementations for ML pipelines: from raw data to predictions Photo by Rodion Kutsaiev on Unsplash Real-life machine learning involves a series of tasks to prepare the data before the magic predictions take place. Those are the features and their respective data types: Image 1 —Features and data types.

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Knowledge Hut

APRIL 25, 2024

However, with Business intelligence dashboards, knowledge is dispersed throughout the organization, enabling users to produce interactive reports, utilize data visualization, and disseminate the knowledge with internal and external stakeholders. The IT departments no longer have exclusive access to information.

Business Intelligence 52

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Edureka

JULY 4, 2024

Overwhelmed with log files and sensor data? It is a cloud-based service by Amazon Web Services (AWS) that simplifies processing large, distributed datasets using popular open-source frameworks, including Apache Hadoop and Spark. Businesses can run these workflows on a recurring basis, which keeps data fresh and analysis-ready.

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Striim

NOVEMBER 17, 2023

Prerequisites Before we embark on the journey of integrating Striim with Google BigQuery ML for real-time data processing in machine learning, there are a few prerequisites that you should ensure are in place. Striim Instance: To get started, you need to have a Striim instance created and have access to it. MODEL ancient-yeti-175123.DMS_SAMPLE.striim_bq_model,

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Machine Learning Data Process PostgreSQL Process 52

Knowledge Hut

NOVEMBER 27, 2023

A data scientist’s job needs loads of exploratory data research and analysis on a daily basis with the help of various tools like Python, SQL, R, and Matlab. This role is an amalgamation of art and science that requires a good amount of prototyping, programming and mocking up of data to obtain novel outcomes.

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Data Science Datasets Machine Learning Portfolio 52

Knowledge Hut

JULY 28, 2023

DL models automatically learn features from raw data, eliminating the need for explicit feature engineering. Data Requirements ML models typically require more labelled training data to achieve good performance. Machine Learning vs Deep Learning: Used for Let us now see when to use deep learning vs machine learning.

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Towards Data Science

FEBRUARY 19, 2024

books, but there are millions in the Openlibrary data set , and I thought it was worthwhile to try adding more options to the search space. First we pull out the relevant columns from the raw data file. The important step here is turning the various functions that we need to apply to the data into Spark UDFs.

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AWS Building Python Bytes 59

Edureka

JULY 5, 2024

Tableau Prep has brought in a new perspective where novice IT users and power users who are not backward faithfully can use drag and drop interfaces, visual data preparation workflows, etc., simultaneously making raw data efficient to form insights. BigQuery), or another data storage solution. Excel), a cloud server (e.g.,

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Data Preparation Process BI ETL Tools 40

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. Transformation section.

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Data Lake Architecture IT Amazon Web Services 52

DataKitchen

MAY 4, 2023

Data Mesh Bergh explained that the Data Mesh organizes a team’s work into chunks called decentralized domains. Instead of boiling the ocean and focusing on all datasets and customers, the Data Mesh focuses on fewer datasets and customers, which reduces complexity and helps get more done.

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Raw Data Data Datasets Data Engineer 52

Knowledge Hut

DECEMBER 7, 2023

Given the rising importance of data with each passing day, I believe I will continue doing so in the coming years. Introducing Microsoft Power BI , a leading solution in this domain, which enables users to transform raw data into insightful visualizations and reports. Power BI allows you access to so many opportunities.

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