Knowledge Hut

JANUARY 19, 2024

The process of gathering, storing, mining, and analyzing data comes under business intelligence. Under BI, all the data a company generates gets stored and used to make significant business growth decisions and multiply the revenue. What is Business Intelligence? What is Business Intelligence?

Business Intelligence 52

Business Intelligence BI Raw Data Data Warehouse 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer in the Data Science team is responsible for this sort of data manipulation. 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.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Hepta Analytics

FEBRUARY 14, 2022

This week, we got to think about our data ingestion design. We looked at the following: How do we ingest – ETL vs ELT Where do we store the data – Data lake vs data warehouse Which tool to we use to ingest – cronjob vs workflow engine NOTE : This weeks task requires good internet speed and good compute.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Knowledge Hut

FEBRUARY 27, 2023

Engineers work with Data Scientists to help make the most of the data they collect and have deep knowledge of distributed systems and computer science. In large organizations, data engineers concentrate on analytical databases, operate data warehouses that span multiple databases, and are responsible for developing table schemas.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Snowflake

APRIL 5, 2023

Two different data modeling approaches—dimensional data modeling and Data Vault—each have their own pros and cons. Modernizing a data warehouse with Snowflake Data Cloud is a smart investment that can provide significant benefits to businesses of all sizes, today more than ever as data models become ever more complex.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

Knowledge Hut

OCTOBER 30, 2023

For any organization to grow, it requires business intelligence reports and data to offer insights to aid in decision-making. This data and reports are generated and developed by Power BI developers. The work of a Power BI developer is to take data in its raw form, derive meaning, and make sense of it.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

ProjectPro

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Knowledge Hut

JUNE 30, 2023

The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. You can pace your learning by joining data engineering courses such as the Bootcamp Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

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 Data Cleanse 52

Knowledge Hut

SEPTEMBER 28, 2023

It stands as a formidable business intelligence tool, providing an end-to-end solution for diverse data needs. This versatile tool handles data extraction, transformation, presentation, and sharing while granting you full control over the information you disseminate.

BI 52

BI Business Intelligence Certification Raw Data 52

Knowledge Hut

APRIL 25, 2024

However, with Business intelligence dashboards, knowledge is dispersed throughout the organization, enabling users to produce interactive reports, utilize data visualization, and disseminate the knowledge with internal and external stakeholders. What is a Business Intelligence Dashboard?

Business Intelligence 52

Business Intelligence BI Raw Data Data Lake 52

Knowledge Hut

DECEMBER 26, 2023

The strategic, tactical, and operational business decisions of a company are directly impacted by Business intelligence. BI encourages using historical data to promote fact-based decision-making instead of assumptions and intuition. What is Business Intelligence (BI)?

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Grouparoo

JANUARY 26, 2022

Warehouse Storage Needs The foundation of Maslow’s hierarchy of needs is about physiological needs like having enough food, water, and sleep. In the world of the modern data stack, the parallel is having a data warehouse that can act as a foundation for the work to be done. It can certainly be quite challenging.

Data Warehouse 52

Data Warehouse Food ETL Tools Raw Data 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Monte Carlo

JUNE 28, 2022

Over the past several years, cloud data lakes like Databricks have gotten so powerful (and popular) that according to Mordor Intelligence , the data lake market is expected to grow from $3.74 Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 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. What about a frantic email from your CTO about “duplicate data” in a business intelligence dashboard? Rise of the Data Lakehouse Data warehouse or data lake?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Edureka

SEPTEMBER 11, 2023

Businesses have more data than ever, including how customers interact with them and what they do on social media, as well as how much inventory they have and how much money they make. In this situation, Business Intelligence (BI) platforms become an important way to make sense of all this data.

Business Intelligence 52

Business Intelligence BI Database-centric Raw Data 52

Knowledge Hut

DECEMBER 28, 2023

The Azure Data Engineer certification imparts to them a deep understanding of data processing, storage and architecture. By leveraging their proficiency, they enable organizations to transform raw data into valuable insights that drive business decisions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

JULY 7, 2022

They codify data needs in a data contract and schemas from consumers up front, and then deliver the data pre-modeled into the data warehouse. It’s becoming clear a data engineering movement is afoot as we have recently covered other organizations taking a similar approach: Convoy and Vimeo.

Data Warehouse 52

Data Warehouse Software Engineer Software Engineering Data 52

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

OCTOBER 27, 2023

With Fabric, users can create their own data warehouse and create quick reports out of them. Power BI is a wonderful tool, and there are many reasons to learn Power BI like: Power BI has a wide range of offers; it is one tool that can perform multiple functions, from data extraction and transformation to dashboard and dynamic reports.

BI 52

BI Project Datasets Healthcare 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. On the other hand, a data warehouse contains historical data that has been cleaned and arranged. . What is Data Warehouse? . Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Knowledge Hut

DECEMBER 26, 2023

Let us first get a clear understanding of why Data Science is important. What is the need for Data Science? If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Monte Carlo

FEBRUARY 15, 2023

Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute. What is a data warehouse?

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Grouparoo

AUGUST 3, 2021

The mission of many data teams is a very simple one. They seek to use data to help the business take smarter actions. The input is raw data from everywhere that touches the business. How can we best get the data into a usable form? Transform : The raw data is often not enough to be useful.

Raw Data 52

Raw Data Data Warehouse SQL Coding 52

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Monte Carlo

APRIL 24, 2023

While we won’t get into the minutia of every consideration for every level of the data stack, it’s important to recall these five considerations as they’ll nonetheless steer the direction of our conversation. Data ingestion When we think about the flow of data in a pipeline, data ingestion is where the data first enters our platform.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Snowflake

FEBRUARY 21, 2023

There’s no need for ETLs, pre-aggregations that sacrifice flexibility, or additional infrastructure that requires data engineering resources. Metrics API: It provides a Metrics API that not only gives meaning to your raw data but also empowers your dev teams across the company to build with a self-service analytics API.

AWS 120

AWS Raw Data Building Architecture 120

AltexSoft

DECEMBER 23, 2022

It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a data lake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.

Process 52

Process Building Raw Data Data Lake 52

dbt Developer Hub

APRIL 19, 2023

The goal of dimensional modeling is to take raw data and transform it into Fact and Dimension tables that represent the business. Part 7: Consume dimensional model ​ Finally, we can consume our dimensional model by connecting to our data warehouse to our Business Intelligence (BI) tools such as Tableau, Power BI, and Looker.

Building 145

Building PostgreSQL BI Database 145

Edureka

JUNE 1, 2023

Data Analytics tools and technologies offer opportunities and challenges for analyzing data efficiently so you can better understand customer preferences, gain a competitive advantage in the marketplace, and grow your business. What is Data Analytics?

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

AltexSoft

JANUARY 26, 2022

If we take the more traditional approach to data-related jobs used by larger companies, there are different specialists doing narrowly-focused tasks on different sides of the project. Data engineers build data pipelines and perform ETL — extract data from sources, transform it, and load it into a centralized repository like a data warehouse.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

U-Next

MARCH 7, 2023

Taking data from sources and storing or processing it is known as data extraction. Define Data Wrangling The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed.

Data Mining 96

Data Mining Scala Government Data Governance 96