Knowledge Hut

APRIL 19, 2023

The process of gathering and compiling data from various sources is known as data Aggregation. Businesses and groups gather enormous amounts of data from a variety of sources, including social media, customer databases, transactional systems, and many more. What is Data Aggregation?

Process 59

Process Data Mining Aggregated Data Portfolio 59

Striim

NOVEMBER 17, 2023

Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring. Striim’s strength lies in its capacity to connect to over 150 data sources, enabling real-time data acquisition from virtually any location and simplifying data transformations.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

AltexSoft

DECEMBER 23, 2022

Integrating data from numerous, disjointed sources and processing it to provide context provides both opportunities and challenges. One of the ways to overcome challenges and gain more opportunities in terms of data integration is to build an ELT (Extract, Load, Transform) pipeline. Order of process phases. What is ELT?

Process 52

Process Building Raw Data Data Lake 52

AltexSoft

AUGUST 25, 2021

And this technology of Natural Language Processing is available to all businesses. Available methods for text processing and which one to choose. Specifics of data used in NLP. What is Natural Language Processing? Here are some big text processing types and how they can be applied in real life. Main NLP use cases.

Process 139

Process Deep Learning Datasets Machine Learning 139

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. The more data we feed, the better the model gets.

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

The Pragmatic Engineer

OCTOBER 17, 2024

  This grant is designed to “support entrepreneurs, tech-geeks, developers, and socially engaged people, who are capable of challenging the way we search and discover information and resources on the internet” The team is tiny; only three people. It’s one front-end dev and two part-time backend devs.

Cloud 273

Cloud Metadata AWS Cloud Computing 273

U-Next

OCTOBER 16, 2022

From business transactions to scientific data, sensor data, pictures, videos, and more, we can and are handling a tremendous amount of information and data every day. The KDD process in data mining is used in business in the following ways to make better managerial decisions: . What is KDD? .

Data Mining 40

Data Mining Process IT Raw Data 40

AltexSoft

DECEMBER 21, 2021

Others believe that such machines simply consume information and learn from it by themselves. Computer systems have limited capabilities without human guidance, and data labeling is the way to teach them to become “smart.” What is data labeling? So, let’s deal with how this process happens. Data collection.

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

Maxime Beauchemin

JANUARY 7, 2018

Batch data processing  — historically known as ETL —  is extremely challenging. In this post, we’ll explore how applying the functional programming paradigm to data engineering can bring a lot of clarity to the process. The greater the claim made using analytics, the greater the scrutiny on the process should be.

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Data Engineering Data Engineer Data Process Process 183

Precisely

NOVEMBER 20, 2023

That means adding context to your internal data by enriching it with information from trusted external sources. Context Is Essential Many organizations fail to attend to the contextual richness of their data before embarking on a new AI initiative. The post Use Data Enrichment to Supercharge AI appeared first on Precisely.

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Raw Data Insurance Data Portfolio 121

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.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Precisely

OCTOBER 5, 2023

According to the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, 77% of data and analytics professionals say data-driven decision-making is the top goal of their data programs. That’s where data enrichment comes in.

Raw Data 69

Raw Data Insurance Datasets Telecommunication 69

Precisely

DECEMBER 13, 2023

Demographic Data Enrichment Matters You probably already have data about the people who visit your website, customers who make purchases at your brick-and-mortar stores, or users of a branded mobile app. Data enrichment vastly increases the value of your customer information, helping you to better understand who makes up your audience.

Raw Data 96

Raw Data Entertainment Data Validation Education 96

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52

Monte Carlo

AUGUST 6, 2024

Integration Layer : Where your data transformations and business logic are applied. Stage Layer: The Foundation The Stage Layer serves as the foundation of a data warehouse. Its primary purpose is to ingest and store raw data with minimal modifications, preserving the original format and content of incoming data.

Data Warehouse 52

Data Warehouse Raw Data BI Machine Learning 52

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 78

Systems Raw Data Metadata Data Cleanse 78

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.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Knowledge Hut

MARCH 7, 2024

Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques. With the rise in opportunities related to Big Data, challenges are also bound to increase. Below are the 5 major Big Data challenges that enterprises face in 2024: 1.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Snowflake

JUNE 20, 2024

In the age of AI, enterprises are increasingly looking to extract value from their data at scale but often find it difficult to establish a scalable data engineering foundation that can process the large amounts of data required to build or improve models. Snowflake customers see an average of 4.6x

Data Engineer 94

Data Engineer Data Engineering Scala Engineering 94

Knowledge Hut

MAY 1, 2024

From tracking the websites we visit - how long, how often - to what we purchase and where we go - our digital footprint is an immense source of data for a lot of businesses. Between our laptops, smartphones and our tablets - almost everything we do translates into some form of data. It sounds like a mighty hefty job, doesn’t it?

Data Science 94

Data Science Raw Data Manufacturing Retail 94

Knowledge Hut

APRIL 26, 2024

Datasets are the repository of information that is required to solve a particular type of problem. Also called data storage areas , they help users to understand the essential insights about the information they represent. In the real world, data sets are huge. Data is not available in a specific format.

Machine Learning 98

Machine Learning Datasets Deep Learning Finance 98

Ripple Engineering

JULY 9, 2024

  Ripple's Journey and Challenges with the Legacy System Our legacy system was once at the forefront of big data processing, but as our operations grew, we faced a tangle of complexities. High maintenance costs and a system that struggled to meet the real-time demands of our data-driven initiatives.

Hadoop 96

Hadoop Data Lake Machine Learning Raw Data 96

Edureka

JUNE 13, 2024

In other words, it acted as an input data source, taking much of the work on data processing and transferring within Power BI. Power Query will automatically execute Query Folding under the following conditions: A data source is an object that can process query requests, just like a database used in most cases.

BI 81

BI Raw Data SQL Database 81

Databand.ai

JULY 6, 2023

Data pipelines are a series of data processing steps that enable the flow and transformation of raw data into valuable insights for businesses. Automating the processes of data engineering can ensure dependable and effective delivery of high-quality information to support decision making.

Data Pipeline 52

Data Pipeline Data Science Raw Data Media 52

Striim

SEPTEMBER 11, 2024

Most importantly, these pipelines enable your team to transform data into actionable insights, demonstrating tangible business value. With data volumes and sources rapidly increasing, optimizing how you collect, transform, and extract data is more crucial to stay competitive. We’ll answer the question, “What are data pipelines?”

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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?

BI 52

BI Raw Data Datasets Business Intelligence 52

Knowledge Hut

JANUARY 19, 2024

For example, all these data sets have information about the consumers' age, gender, and preferences associated with the business. Similarly, the stored data have details about the services or products that are top selling and those not attracting customers. The entire work of BI depends on the data warehouse in an organization.

Business Intelligence 52

Business Intelligence BI Raw Data Data Warehouse 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. Data lakes are often used for situations in which an organization wishes to store information for possible future use.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Knowledge Hut

MAY 1, 2024

Data is everywhere, and we have all seen exponential growth in the data that is generated daily. I nformation must be extracted from this data to make sense of it, and we must gain insights from th is information that will help us to understand repeating patterns.

Algorithm 98

Algorithm Raw Data Data Science Computer Science 98

Cloudyard

JUNE 11, 2024

Ensuring the reliability and resilience of these workflows is critical, especially when dealing with production data pipelines. Imagine you’re tasked with managing a critical data pipeline in Snowflake that processes and transforms large datasets. Task B: Transforms the data in the staging table.

Raw Data 52

Raw Data Aggregated Data Data Pipeline Data Workflow 52

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs. Have I Checked The Raw Data And The Integrated Data?

Raw Data 50

Raw Data Data Ingestion Datasets Data 50

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 86

Engineering Raw Data Data Science Machine Learning 86

Snowflake

MAY 23, 2024

Right now we’re focused on raw data quality and accuracy because it’s an issue at every organization and so important for any kind of analytics or day-to-day business operation that relies on data — and it’s especially critical to the accuracy of AI solutions, even though it’s often overlooked. How did you identify that issue?

Data Pipeline 88

Data Pipeline Raw Data Data Schemas Technology 88

Knowledge Hut

JANUARY 18, 2024

Using advanced analytical tools, a data scientist interprets data and presents it in meaningful information. For more information, check out the best Data Science certification. A data scientist’s job description focuses on the following – Automating the collection process and identifying the valuable data.

Data Science 98

Data Science Business Analyst Data Architect ETL Method 98

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?

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

Hevo

APRIL 27, 2023

In today’s data-driven era, you have more raw data than ever before. However, to leverage the power of big data, you need to convert raw data into valuable insights for informed decision-making. ” While they may sound […]

Raw Data 52

Raw Data Big Data Data Data Warehouse 52

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. In today’s fast-paced business environment, data-driven insights are the lifeblood of staying ahead.

Raw Data 75

Raw Data Utilities Government Data 75