AltexSoft

AUGUST 29, 2023

The term data lake itself is metaphorical, evoking an image of a large body of water fed by multiple streams, each bringing new data to be stored and analyzed. Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Architecture 100

Architecture Metadata Unstructured Data Machine Learning 100

Knowledge Hut

DECEMBER 26, 2023

Many companies often use these Data Science job titles interchangeably, thus, the responsibility involved in a particular job role also depends on the company under consideration. Let us now look at the top 16 roles in Data Science Jobs and their Job descriptions. Data Analyst Scientist.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Scott Logic

NOVEMBER 6, 2023

Neither may be well suited to data science calculations. User/consumer of the data Sometimes a type of processing or query is setup once and managed by developers, but often a person like a business analyst or financial reporter is regularly writing queries and viewing the results.

Data Lake 52

Data Lake Kafka BI Unstructured Data 52

Knowledge Hut

DECEMBER 29, 2023

Big Data is a part of this umbrella term, which encompasses Data Warehousing and Business Intelligence as well. A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

NOVEMBER 28, 2023

Data scientists do more than just model and process structured and unstructured data; they also translate the results into useful strategies for stakeholders. They must work on data architecture, collect and cleanse data from different sources, and conduct research.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

ProjectPro

NOVEMBER 30, 2021

In extract-transform-load (ETL), data is obtained from multiple sources, transformed, and stored in a single data warehouse, with access to data analysts , data scientists , and business analysts for data visualization and statistical analysis model building, forecasting, etc.

Process 52

Process Data Pipeline Data Warehouse AWS 52

AltexSoft

NOVEMBER 23, 2021

Before we get into more detail, let’s determine how data virtualization is different from another, more common data integration technique — data consolidation. Data virtualization vs data consolidation. The example of a typical two-tier architecture with a data lake and data warehouses and several ETL processes.

Process 69

Process Data Lake Metadata Data Warehouse 69

phData: Data Engineering

JANUARY 3, 2022

This likely requires you to aggregate data from your ERP system, your supply chain system, potentially third-party vendors, and data around your internal business structure. This style often isn’t as performant compared to an ELT process, as data for each batch or stream is often required from dependent or related systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52