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. In this article, we’ll focus on a data lake vs. data warehouse.

Data Lake 57

Data Lake Data Warehouse Hadoop Raw Data 57

Monte Carlo

AUGUST 25, 2023

Modern companies are ingesting, storing, transforming, and leveraging more data to drive more decision-making than ever before. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 83

Engineering Raw Data Data Science Scala 83

Snowflake

MAY 23, 2024

In this edition, we’ll learn why the founders of data tools company TDAA, Andrew Curran and Jon Farr, chose Snowflake as the platform to deliver their app Pancake , as well as the ways they’re effectively leveraging the Snowflake Native App model. For many data sources, the schema of the data source can change without warning.

Data Pipeline 85

Data Pipeline Raw Data Data Schemas Technology 85

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

SQL 73

SQL Data Analytics Hadoop Raw Data 73

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

Rockset

JUNE 13, 2019

We love SQL — our mission is to bring fast, real-time queries to messy, semi-structured real-world data and SQL is a core part of our effort. Datagrip , Jupyter , RStudio ) and data exploration / visualization (e.g. A SQL API allows our product to fit neatly into the stacks of our users without any workflow re-architecting.

SQL 52

SQL Structured Data Building Raw Data 52

Knowledge Hut

JUNE 28, 2023

In our data-driven world, our lives are governed by big data. The TV shows we watch, the social media we follow, the news we read, and even the optimized routes we take to work are all influenced by the power of big data analytics. The answer lies in the strategic utilization of business intelligence for data mining (BI).

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

ThoughtSpot

MARCH 5, 2024

Managing complex data pipelines is a major challenge for data-driven organizations looking to accelerate analytics initiatives. While AI-powered, self-service BI platforms like ThoughtSpot can fully operationalize insights at scale by delivering visual data exploration and discovery, it still requires robust underlying data management.

BI 94

BI Datasets Raw Data SQL 94

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Warehouse? . What is Data Lake? .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. 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. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is Data Science? What are the roles and responsibilities of a Data Engineer? What is the need for Data Science?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

JANUARY 18, 2024

I’ve often noticed that people use terms like Data Science and Artificial Intelligence ( AI ) interchangeably. The key connection between Data Science and AI is data. Some may argue that AI and Machine Learning fall within the broader category of Data Science , but it's essential to recognize the subtle differences.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Knowledge Hut

APRIL 25, 2024

One of the industries with the quickest growth rates is big data. It refers to gathering and processing sizable amounts of data to produce insights that may be used by an organization to improve its various facets. You must become familiar with the fundamental elements of big data to comprehend it effectively.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. How much data was generated in a minute in 2013 and 2022.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

JANUARY 11, 2024

Data Science has brought a revolutionary change in the way different industries work. I’ve observed that ever since data science techniques and approaches, including data science for finance, have made their way into different industrial domains, the growth has been tremendous. What Is Data Science?

Finance 93

Finance Data Science Programming Language Machine Learning 93

AltexSoft

JUNE 26, 2023

All successful companies do it: constantly collect data. 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. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. This article revisits the foundational elements of ELT, exploring what it is, how it reshaped data strategies, and how it works.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

ProjectPro

FEBRUARY 16, 2023

ETL is a critical component of success for most data engineering teams, and with teams harnessing it with the power of AWS, the stakes are higher than ever. Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand.

AWS 52

AWS Data Management ETL Tools Management 52

Knowledge Hut

JANUARY 19, 2024

Entering the world of data science is a strategic move in the 21st century, known for its lucrative opportunities. With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. Recognizing the growing need for data scientists, institutions worldwide are intensifying efforts to meet this demand.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Edureka

AUGUST 2, 2023

In this digital transformation era, data is at the heart of decision-making. Data science has gained prominence, playing a crucial role in deriving insights from vast volumes of data. Aspiring data scientists must familiarize themselves with the best programming languages in their field.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Towards Data Science

MAY 14, 2024

Dataform enables the application of software engineering best practices such as testing, environments, version control, dependencies management, orchestration and automated documentation to data pipelines. js for data transformations and logic. Release configuration is the automated process by which this compilation takes place.

Data Pipeline 72

Data Pipeline Coding Raw Data Accessible 72

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

Hepta Analytics

FEBRUARY 14, 2022

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 27, 2024

Data tracking is becoming more and more important as technology evolves. A global data explosion is generating almost 2.5 quintillion bytes of data today, and unless that data is organized properly, it is useless. What Is Big Data Analytics? Some important big data processing platforms are: Microsoft Azure.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Edureka

JANUARY 18, 2024

This guide provides a comprehensive understanding of the essential skills and knowledge required to become a successful data scientist, covering data manipulation, programming, mathematics, big data, deep learning, and machine learning technologies. Table of Contents Introduction to Data Science What is Data Science?

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

Knowledge Hut

SEPTEMBER 26, 2023

The demand for data professionals with business intelligence skills has increased significantly in recent years. With technological advancements and digital transformations, businesses are taking data very seriously. In today's business environment, data is an invaluable asset.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

Knowledge Hut

JANUARY 18, 2024

Data science insights allow enterprises to succeed, make better decisions, and increase customer satisfaction. Insights in data science are the deep understanding acquired by an individual or organization as a result of examining information on a particular subject. Without analytics, data is meaningless. What are Analytics?

Data Science 52

Data Science Media Food Data 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52