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 Platform for shopfloor management and data sources such like MES, ERP, PLM and machine data.

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Data Science Dojo

SEPTEMBER 11, 2024

Microsoft Fabric aims to reduce unnecessary data replication, centralize storage, and create a unified environment with its unique data fabric method. Microsoft Fabric is a cutting-edge analytics platform that helps data experts and companies work together on data projects. What is Microsoft Fabric?

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Power BI Data Pipeline Data Warehouse Data Engineering 284

Analytics Vidhya

MARCH 10, 2023

It is intended to be a fully managed, multi-cloud solution that does not need clients to handle hardware or software. Instead, it provides high-performance analytics, flexibility, and cost-effective scaling. Snowflake’s design is […] The post Top 6 Snowflake Interview Questions appeared first on Analytics Vidhya.

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Analytics Vidhya

MARCH 5, 2023

HDInsight works seamlessly with the Hadoop ecosystem, which includes technologies like MapReduce, Hive, […] The post Top 6 Microsoft HDFS Interview Questions appeared first on Analytics Vidhya.

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Data Science Blog

SEPTEMBER 19, 2023

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures? appeared first on Data Science Blog.

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Analytics Vidhya

MAY 24, 2023

From physical hard drives to cloud computing, unravel the captivating world of data storage and recognize its ever-evolving role in our […] The post What is Data Storage and How is it Used? appeared first on Analytics Vidhya.

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Cloud Computing Analytics Analytics Data Engineering 281

Data Science Blog

NOVEMBER 15, 2023

New big data architectures and, above all, data sharing concepts such as Data Mesh are ideal for creating a common database for many data products and applications. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg. Click to enlarge!

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Data Models Data Modeling Business Intelligence Business Intelligence 245

ODSC - Open Data Science

FEBRUARY 6, 2024

Data engineering has become an integral part of the modern tech landscape, driving advancements and efficiencies across industries. So let’s explore the world of open-source tools for data engineers, shedding light on how these resources are shaping the future of data handling, processing, and visualization.

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phData

SEPTEMBER 29, 2023

When you think of data engineering , what comes to mind? In reality, though, if you use data (read: any information), you are most likely practicing some form of data engineering every single day. Said differently, any tools or steps we use to help us utilize data can be considered data engineering.

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Smart Data Collective

JUNE 20, 2022

When data leaders move to the cloud, it’s easy to get caught up in the features and capabilities of various cloud services without thinking about the day-to-day workflow of data scientists and data engineers. Failing to make production data accessible in the cloud.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Additional integrations with services like Amazon Data Firehose , AWS Glue , and Amazon Athena allowed for historical reporting, user activity analytics, and sentiment trends over time through Amazon QuickSight. She has extensive experience in data and analytics, application development, infrastructure engineering, and DevSecOps.

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phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Much of what is discussed in this guide will assume some level of analytics strategy has been considered and/or defined. No problem!

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Smart Data Collective

OCTOBER 17, 2022

While growing data enables companies to set baselines, benchmarks, and targets to keep moving ahead, it poses a question as to what actually causes it and what it means to your organization’s engineering team efficiency. What’s causing the data explosion? Explosive data growth can be too much to handle.

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Big Data Big Data Data Engineering Data Engineering 119

Data Science Blog

MAY 15, 2023

Azure Synapse Analytics: Azure Synapse Analytics ist ein verwalteter Analysedienst, der eine einheitliche Erfahrung für Big Data und Data Warehousing bietet. Data Fusion bietet eine Vielzahl von Funktionen zur Datenaufnahme, -umwandlung und -verarbeitung und kann mit einer Vielzahl von Datenquellen verwendet werden.

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phData

MARCH 20, 2023

Length of Interview: 30 – 45 minutes Interview 2: Leadership In this interview, you will meet with the Director of the Solutions Engineering team. The discussion points in this interview will include a review of your current experience as it relates to cloud data engineering and solution engineering.

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Cloud Data Azure Data Engineering Data Engineer 98

phData

MARCH 8, 2023

Fivetran is an automated data integration platform that offers a convenient solution for businesses to consolidate and sync data from disparate data sources. With over 160 data connectors available, Fivetran makes it easy to move data out of, into, and across any cloud data platform in the market.

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Flipboard

NOVEMBER 24, 2023

This offering enables BMW ML engineers to perform code-centric data analytics and ML, increases developer productivity by providing self-service capability and infrastructure automation, and tightly integrates with BMW’s centralized IT tooling landscape.

ML 154

ML ML AWS AI 154

phData

NOVEMBER 8, 2024

These systems are built on open standards and offer immense analytical and transactional processing flexibility. Adopting an Open Table Format architecture is becoming indispensable for modern data systems. Schema Evolution Data structures are rarely static in fast-moving environments. Why are They Essential?

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Data Science Blog

MARCH 14, 2023

Von Big Data über Data Science zu AI Einer der Gründe, warum Big Data insbesondere nach der Euphorie wieder aus der Diskussion verschwand, war der Leitspruch “S**t in, s**t out” und die Kernaussage, dass Daten in großen Mengen nicht viel wert seien, wenn die Datenqualität nicht stimme.

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Towards AI

JANUARY 28, 2024

To start, get to know some key terms from the demo: Snowflake: The centralized source of truth for our initial data Magic ETL: Domo’s tool for combining and preparing data tables ERP: A supplemental data source from Salesforce Geographic: A supplemental data source (i.e., Instagram) used in the demo Why Snowflake?

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ETL Python Database Data Preparation 111

phData

FEBRUARY 21, 2025

A data warehouse acts as a single source of truth for an organization’s data, providing a unified view of its operations and enabling data-driven decision-making. A data warehouse enables advanced analytics, reporting, and business intelligence. On the other hand, cloud data warehouses can scale seamlessly.

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ODSC - Open Data Science

JANUARY 26, 2024

However, we are making a few changes, most importantly, ODSC East will feature 2 co-located summits, The Data Engineering Summit , and the Ai X Generative AI Summit. In-person attendees will have access to the Ai X Generative Summit and the Data Engineering Summit.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

Data Science Blog

SEPTEMBER 3, 2024

Einer der ersten dieser Anbieter war das Unternehmen PAF (Process Analytics Factory) mit dem Power BI Plugin namens PAFnow, welches von Celonis aufgekauft wurde und heute anscheinend (?) Reduzierte Personalkosten , sind oft dann gegeben, wenn interne Data Engineers verfügbar sind, die die Datenmodelle intern entwickeln.

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Data Science Power BI Azure Data Warehouse 130

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

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Data Science Machine Learning Machine Learning Data Visualization 150

phData

JULY 24, 2024

Creating personalized marketing campaigns is by far the best option, but only if your analytics are curated and organized properly for accurate analysis. phData helps enterprises create personalized campaigns by analyzing customers’ data to segment them into separate audiences that may react similarly to campaigns. Why phData?

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Machine Learning Machine Learning Data Engineering Data Engineering 52

phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. What is the Modern Data Stack? Data modeling, data cleanup, etc.

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Data Science Blog

JUNE 27, 2023

Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture.

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Big Data Big Data Apache Kafka Database 130

phData

JUNE 26, 2024

Cleaning and preparing the data Raw data typically shouldn’t be used in machine learning models as it’ll throw off the prediction. Data engineers can prepare the data by removing duplicates, dealing with outliers, standardizing data types and precision between data sets, and joining data sets together.

Machine Learning 52

Machine Learning Machine Learning Data Engineering Data Engineering 52

Alation

OCTOBER 18, 2022

Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Making this data visible in the data catalog will let data teams share their work, support re-use, and empower everyone to better understand and trust data.

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IBM Journey to AI blog

MAY 15, 2024

Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models. Unified, governed data can also be put to use for various analytical, operational and decision-making purposes. This process is known as data integration, one of the key components to a strong data fabric.

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Data Pipeline ETL SQL Database 85

ODSC - Open Data Science

JUNE 16, 2023

Data security posture management is particularly beneficial for organizations that have committed to a cloud-first vision and are moving away from a mixed cloud/on-premises infrastructure. Automatically find and categorize data across all clouds. Avoid exposing cloud data and reduce the attack surface.

Cloud Data 52

Cloud Data Data Science Database Data Scientist 52

phData

MARCH 29, 2023

However, many analysts and other data professionals run into two common problems: They are not given direct access to their database They lack the skills in SQL to write the queries themselves The traditional solution to these problems is to rely on IT and data engineering teams. What can be done? What is KNIME?

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Database SQL Analytics Analytics 52

IBM Journey to AI blog

JULY 17, 2023

Within watsonx.ai, users can take advantage of open-source frameworks like PyTorch, TensorFlow and scikit-learn alongside IBM’s entire machine learning and data science toolkit and its ecosystem tools for code-based and visual data science capabilities. ” Vitaly Tsivin, EVP Business Intelligence at AMC Networks.

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AI AI Machine Learning Machine Learning 74

Alation

JUNE 21, 2022

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. Data engineers want to catalog data pipelines.

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DataOps Data Scientist Data Quality Data Pipeline 52

AWS Machine Learning Blog

OCTOBER 18, 2023

Rushikesh Jagtap is a Solutions Architect with 5+ years of experience in AWS Analytics services. He is passionate about helping customers to build scalable and modern data analytics solutions to gain insights from the data. Outside of work, he loves watching Formula1, playing badminton, and racing Go Karts.

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phData

JULY 23, 2024

All these data points could be used in an analytical dashboard to estimate the likelihood that the patient will have a medical episode or be used to determine if they have a disease that may have gone undiagnosed. Expertise Here at phData, we strive to be experts in data engineering, analytics, and machine learning.

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Machine Learning Machine Learning Data Engineering Data Engineer 52

phData

AUGUST 6, 2024

Organizations must ensure their data pipelines are well designed and implemented to achieve this, especially as their engagement with cloud data platforms such as the Snowflake Data Cloud grows. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

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