phData

AUGUST 9, 2023

In short, ELT exemplifies the data strategy required in the era of big data, cloud, and agile analytics. With ELT, we first extract data from source systems, then load the raw data directly into the data warehouse before finally applying transformations natively within the data warehouse.

ETL 52

ETL Data Warehouse Cloud Data Big Data 52

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. This will open the ML transforms page.

AWS 92

AWS ML ML ETL 92

Dataconomy

SEPTEMBER 4, 2023

Big data analytics: Big data analytics is designed to handle massive volumes of data from various sources, including structured and unstructured data. Big data analytics is essential for organizations dealing with large-scale data, such as social media platforms, e-commerce giants, and scientific research.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 52

Pickl AI

JULY 6, 2023

Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis. It applies the data structure during querying rather than data ingestion. Processing of Data Once the data is stored, Hive provides a metadata layer allowing users to define the schema and create tables.

Hadoop 52

Hadoop SQL Big Data Big Data 52

ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential.

Analytics 52

Analytics Analytics Data Analyst SQL 52

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. They must also ensure that data privacy regulations, such as GDPR and CCPA , are followed.

Data Engineering 91

Data Engineering Data Engineer Data Engineering Data Engineering 91

Pickl AI

APRIL 6, 2023

Data Engineering is one of the most productive job roles today because it imbibes both the skills required for software engineering and programming and advanced analytics needed by Data Scientists. How to Become an Azure Data Engineer? Data Warehousing concepts and knowledge should be strong.

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

Tableau

MARCH 30, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. March 30, 2021.

Azure 99

Azure Tableau Data Lakes SQL 99

Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. A point of data entry in a given pipeline. K2View leaps at the traditional approach to ETL and ELT tools.

Data Pipeline 131

Data Pipeline Data Warehouse ETL Exploratory Data Analysis 131

Tableau

MARCH 29, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere. March 30, 2021.

Azure 52

Azure Tableau Data Lakes SQL 52

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

AWS 83

AWS Data Lakes Clustering Data Preparation 83

Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69