Knowledge Hut

MAY 1, 2024

If the general idea of stand-up meetings and sprint meetings is not taken into consideration, a day in the life of a data scientist would revolve around gathering data, understanding it, talking to relevant people about the data, asking questions about it, reiterating the requirement and the end product, and working on how it can be achieved.

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Knowledge Hut

MARCH 7, 2024

The greatest data processing challenge of 2024 is the lack of qualified data scientists with the skill set and expertise to handle this gigantic volume of data. Inability to process large volumes of data Out of the 2.5 quintillion data produced, only 60 percent workers spend days on it to make sense of it.

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Cloudera

NOVEMBER 19, 2020

The modeling process begins with data collection. Here, Cloudera Data Flow is leveraged to build a streaming pipeline which enables the collection, movement, curation, and augmentation of raw data feeds. These feeds are then enriched using external data sources (e.g.,

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Cloudera

FEBRUARY 21, 2023

The one requirement that we do have is that after the data transformation is completed, it needs to emit JSON. data transformations can be defined using the Kafka Table Wizard. This might be OK for some cases.

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AltexSoft

MAY 12, 2022

Audio data transformation basics to know. Before diving deeper into processing of audio files, we need to introduce specific terms, that you will encounter at almost every step of our journey from sound data collection to getting ML predictions. One of the largest audio data collections is AudioSet by Google.

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The Modern Data Company

FEBRUARY 2, 2024

Ever wondered why building data-driven applications feels like an uphill battle? It’s not just you – turning raw data into something meaningful can be a real challenge. This prolonged timeline is not just a minor inconvenience; it is the bottleneck that hampers responsiveness and agility in decision-making.

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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

JULY 4, 2023

It involves extracting meaningful features from the data and using them to make informed decisions or predictions. Data Collection and Pre-processing The first step is to collect the relevant data that contains the patterns of interest. The steps involved in it can be summarized as follows: 1.

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Knowledge Hut

JANUARY 18, 2024

Data is an important feature for any organization because of its ability to guide decision-making based on facts, statistical numbers, and trends. Data Science is a notion that entails data collection, processing, and exploration, which leads to data analysis and consolidation.

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Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

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WeCloudData

OCTOBER 19, 2021

Methodology In order to meet the technical requirements for recommender system development as well as other emerging data needs, the client has built a mature data pipeline through the use of cloud platforms like AWS in order to store user clickstream data, and Databricks in order to process the raw data.

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WeCloudData

OCTOBER 19, 2021

Methodology In order to meet the technical requirements for recommender system development as well as other emerging data needs, the client has built a mature data pipeline through the use of cloud platforms like AWS in order to store user clickstream data, and Databricks in order to process the raw data.

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Monte Carlo

MARCH 12, 2025

Data Versioning: Want to know how your data changed over time? Improved Performance: Raw data lakes can be slow since they require scanning every file during a search. Delta Lake speeds things up by optimizing queries, giving you faster results without locking you into a rigid data warehouse. Why Data Lake?

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Knowledge Hut

JANUARY 18, 2024

The role can also be defined as someone who has the knowledge and skills to generate findings and insights from available raw data. Data Engineer A professional who has expertise in data engineering and programming to collect and covert raw data and build systems that can be usable by the business.

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Data Engineering Weekly

FEBRUARY 26, 2023

Identify and study the raw data. Modeling Test and optimize the output Productionise into a usable format [link] Sponsored: Replacing GA4 with Analytics on your Data Cloud The GA4 migration deadline is fast approaching. Join our webinar to learn how you can replace GA with analytics on your data cloud.

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Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. What does a Data Processing Analysts do ?

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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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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. Data Sources: How different are your data sources?

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Databand.ai

JUNE 8, 2023

By implementing an observability pipeline, which typically consists of multiple technologies and processes, organizations can gain insights into data pipeline performance, including metrics, errors, and resource usage. This ensures the reliability and accuracy of data-driven decision-making processes.

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Data Engineering Weekly

MAY 8, 2023

Receipt table (later referred to as table_receipts_index): It turns out that all the receipts were manually entered into the system, which creates unstructured data that is error-prone. This data collection method was chosen because it was simple to deploy, with each employee responsible for their own receipts.

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Scott Logic

APRIL 30, 2024

This data is typically used by system apps to inform users when apps are disproportionately draining their battery and provide estimates of remaining battery hours depending on their personal usage. We use power to monitor the power Our data collection service is clearly going to be consuming some power when collecting energy values.

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The Modern Data Company

APRIL 15, 2024

Transforming Data Complexity into Strategic Insight At first glance, the process of transforming raw data into actionable insights can seem daunting. The journey from data collection to insight generation often feels like operating a complex machine shrouded in mystery and uncertainty.

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Knowledge Hut

APRIL 25, 2023

You can find a comprehensive guide on how data ingestion impacts a data science project with any Data Science course. Why Data Ingestion is Important? Data ingestion provides certain benefits to the business: The raw data coming from various sources is highly complex. Why Data Ingestion is Important?

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Knowledge Hut

JULY 28, 2023

DL models automatically learn features from raw data, eliminating the need for explicit feature engineering. Machine Learning vs Deep Learning: Feature Engineering ML algorithms require manual feature engineering, where domain experts extract and engineer relevant features from the data.

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Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily.

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Grouparoo

JANUARY 11, 2022

The fundamental purpose of a data warehouse is the aggregation of information from diverse sources to inform data-driven decision-making processes. What is a Data Lake? There is no processing to integrate and manage data, including quality checks or detect inconsistencies, duplications, or discrepancies.

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Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. As data collection and usage have become more sophisticated, the sources of data have become a lot more varied and disparate, volumes have grown and velocity has increased.

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Knowledge Hut

APRIL 19, 2023

Levels of Data Aggregation Now lets look at the levels of data aggregation Level 1: At this level, unprocessed data are collected from various sources and put in one source. Level 2: At this stage, the raw data is processed and cleaned to get rid of inconsistent data, duplicates values, and error in datatype.

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Ascend.io

JANUARY 2, 2024

The key differentiation lies in the transformational steps that a data pipeline includes to make data business-ready. Ultimately, the core function of a pipeline is to take raw data and turn it into valuable, accessible insights that drive business growth. cleaning, formatting)?

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Knowledge Hut

FEBRUARY 7, 2023

We use different SAS statements for reading the data, cleaning and manipulating it in the data step prior to analyzing it. The raw data gets transformed into a SAS dataset during the data stage. SAS library Remote access for data sources such as Azure, SAS catalogue, Hadoop, S3, zip and more. 

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Grouparoo

NOVEMBER 29, 2021

For example, service agreements may cover data quality, latency, and availability, but they are outside the organization's control. Primary Data Sources are those where data collection is from its point of creation before any processing. It may be raw data, validated data, or big data.

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Knowledge Hut

JULY 31, 2023

In 2023, Business Intelligence (BI) is a rapidly evolving field focusing on data collection, analysis, and interpretation to enhance decision-making in organizations. Careful consideration of research methodology, data collection methods, and analysis techniques helps in ensuring the validity and reliability of your findings.

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ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions. Who is a Data Scientist?

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AltexSoft

DECEMBER 21, 2021

.” In this article, you will find out what data labeling is, how it works, which data labeling types exist, and what best practices to follow to make this process smooth as glass. What is data labeling? A label or a tag is a descriptive element that tells a model what an individual data piece is so it can learn by example.

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Knowledge Hut

APRIL 23, 2024

Data plays a crucial role in identifying opportunities for growth and decision-making in today's business landscape. Business intelligence collects techniques, tools, and methodologies organizations use to transform raw data into valuable information and meaningful insights. Automation can help businesses in several ways.

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Knowledge Hut

JANUARY 24, 2024

They employ a wide array of tools and techniques, including statistical methods and machine learning, coupled with their unique human understanding, to navigate the complex world of data. A significant part of their role revolves around collecting, cleaning, and manipulating data, as raw data is seldom pristine.

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Edureka

AUGUST 29, 2024

In this respect, the purpose of the blog is to explain what is a data engineer , describe their duties to know the context that uses data, and explain why the role of a data engineer is central. What Does a Data Engineer Do? Design algorithms transforming raw data into actionable information for strategic decisions.

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