Towards Data Science

APRIL 3, 2023

But this article will closely examine some of the most prominent near(ish) future ideas that may become part of the post-modern data stack as well as their potential impact on data engineering. Zero-ETL What it is : A misnomer for one thing; the data pipeline still exists. No duplicate data storage.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

AltexSoft

MAY 12, 2023

Of course, tapping into this immense pool of unstructured data may offer businesses a wealth of opportunities to better understand their customers, markets, and operations, ultimately driving growth and success. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Ascend.io

JANUARY 2, 2024

But let’s be honest, creating effective, robust, and reliable data pipelines, the ones that feed your company’s reporting and analytics, is no walk in the park. From building the connectors to ensuring that data lands smoothly in your reporting warehouse, each step requires a nuanced understanding and strategic approach.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

AltexSoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data democratization.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

NOVEMBER 2, 2023

Azure Data Engineers and Azure DevOps Engineers are two critical components of the Azure ecosystem for different but interconnected reasons. An Azure Data Engineer is a professional responsible for designing, implementing, and managing data solutions using Microsoft's Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Ascend.io

SEPTEMBER 14, 2023

As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. In this article, our primary focus will be to unpack the reasons behind Python’s prominence in the data engineering domain. Why Python for Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

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. This article explores prominent research subjects within BI for 2023. They manage data access, monitor data quality, and enforce data protection measures.

Business Intelligence 52

Business Intelligence BI Data Mining Data Collection 52

Knowledge Hut

DECEMBER 26, 2023

What is Data Science? What are the roles and responsibilities of a Data Engineer? How does one become a Data engineer, and what skills are required? Our primary focus in this article will be to answer all these questions and take you a step forward towards your dream of becoming a Data engineer. And many more.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Grouparoo

NOVEMBER 29, 2021

Alternatively, this can be data generated by another process and then made available for subsequent processing. Therefore, the source data may be raw, unfiltered, and unrefined, or polished and fully formed. In this article, we'll look at the definition of data sources and their general types.

Raw Data 40

Raw Data Big Data Relational Database Data Warehouse 40

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. What Is Big Data Analytics?

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

NOVEMBER 16, 2023

Cloud computing, along with data science has been the buzzword for quite some time now. Companies have moved towards cloud architecture for their data storage and computing needs. This article illustrates the blend between a data scientist and Azure as a cloud platform. which are shaping data science applications.

Data Science 52

Data Science Technology Programming Language Cloud Computing 52

Monte Carlo

AUGUST 19, 2023

To make things a little easier, I’ve outlined the six must-have layers you need to include in your data platform and the order in which many of the best teams choose to implement them. The five must-have layers of a modern data platform Second to “how do I build my data platform?”, Image courtesy of Monte Carlo.

Building 52

Building BI Data Lake Data Governance 52

Knowledge Hut

FEBRUARY 7, 2023

SAS, on the other hand, is about 50-year-old proprietary data science tool catering to the industry's demands. Let us explore more about SAS as a tool, SAS programming and SAS certification in this article.  These statements in a SAS program are broadly classified as data steps and procedures. What is SAS?  California (USA).

Data Science 52

Data Science Datasets SQL Data Mining 52

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.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Another type of data storage — a data lake — tried to address these and other issues. Data lake. Lakehouse architecture.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

JULY 29, 2022

What does it take to store all New York Times articles published between 1855 and 1922? Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Source: The Wall Street Journal.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Ascend.io

MAY 18, 2023

However, the modern data stack landscape continues to evolve, and managing and scaling these tools exacerbates the gaps between them. As demand for data grows, delivering value efficiently and at speed becomes increasingly challenging. Companies no longer had to worry about storage and compute costs or limited access to their data.

Data Warehouse 52

Data Warehouse Data Pipeline Data Lake Data Engineering 52

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

SEPTEMBER 10, 2021

Information often resides across countless distributed data sources, resulting in data silos. To get a single unified view of all information, companies opt for data integration. What is data integration and why is it important? A newer way to integrate data into a centralized location is ELT. Data replication.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

Snowflake

APRIL 5, 2023

Traditionally, the dimensional data modeling approach is used to build complex data warehouses, while Data Vaults are used in data warehouses to offer long-term historical data storage while modeling. Why is data modeling important for a data warehouse?

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. Your CTO is excited about migrating to the cloud, and constantly sends your team articles highlighting performance measurements against some of the latest technologies.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

AltexSoft

SEPTEMBER 23, 2021

Evidently, common storage solutions fail to provide a unified data view and meet the needs of companies for seamless data flow. One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. Azure Data Factory.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Ascend.io

APRIL 12, 2023

There is no consensus about what data quality is, how to measure it, and how to even approach implementing it. In the correct storage. Coming from and being written to the correct physical file system location, database tables and columns, or other types of data storage systems. Arriving in the correct cadence.

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Monte Carlo

JULY 30, 2020

Unlike traditional monolithic data infrastructures that handle the consumption, storage, transformation, and output of data in one central data lake, a data mesh supports distributed, domain-specific data consumers and views “data-as-a-product,” with each domain handling their own data pipelines.

IT 45

IT Data Lake Business Intelligence Data Architecture 45

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0 It introduces Hadoop 2.0

Hadoop 40

Hadoop Big Data Architecture Metadata 40

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

Hadoop 52

Hadoop Project Big Data Healthcare 52