Databand.ai

JULY 19, 2023

The Transform Phase During this phase, the data is prepared for analysis. This preparation can involve various operations such as cleaning, filtering, aggregating, and summarizing the data. The goal of the transformation is to convert the raw data into a format that’s easy to analyze and interpret.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

The Modern Data Company

MAY 10, 2023

Data governance and security: Evaluate the native security, data governance, and data quality management features. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Data governance and security: Evaluate the native security, data governance, and data quality management features. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Data governance and security: Evaluate the native security, data governance, and data quality management features. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Knowledge Hut

APRIL 25, 2024

When done correctly, data integration can enhance data quality, free up resources, lower IT costs, and stimulate creativity without significantly modifying current applications or data structures. Data Governance Data governance is the process of ensuring that data is trustworthy, accurate, available, and usable.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 83

Engineering Raw Data Data Science Scala 83

DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data.

Data Lake 52

Data Lake Building Raw Data ETL Tools 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?”,

Building 52

Building BI Data Lake Data Governance 52

Knowledge Hut

APRIL 23, 2024

Sentiment Analysis and Natural Language Processing (NLP): AI and ML algorithms can process and analyze unstructured data, like text and speech, to better understand consumer sentiments. This entails constant surveillance, threat detection, and the adoption of strict security procedures all along the data lifecycle.

Big Data 52

Big Data Retail Recruitment Transportation 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

AltexSoft

AUGUST 29, 2023

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. This article explains what a data lake is, its architecture, and diverse use cases. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

ProjectPro

JANUARY 27, 2023

You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Data Warehousing - ETL tools and processes can be leveraged to load data into a data warehouse for reporting and analysis.

BI 52

BI ETL Tools Retail Healthcare 52

AltexSoft

SEPTEMBER 23, 2021

A data hub, in turn, is rather a terminal or distribution station: It collects information only to harmonize it, and sends it to the required end-point systems. Data lake vs data hub. A data lake is quite opposite of a DW, as it stores large amounts of both structured and unstructured data.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Monte Carlo

APRIL 1, 2021

Data Catalogs Can Drown in a Data Lake Although exceptionally flexible and scalable, data lakes lack the organization necessary to facilitate proper metadata management and data governance. Data discovery tools and platforms can help. Image courtesy of Adrian on Unsplash.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 80

Data Lake Analytics Application Cloud Storage Architecture 80

AltexSoft

NOVEMBER 10, 2021

Traditional data warehouse platform architecture. Key data warehouse limitations: Inefficiency and high costs of traditional data warehouses in terms of continuously growing data volumes. Inability to handle unstructured data such as audio, video, text documents, and social media posts. Data lake.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

JUNE 14, 2023

Amazon S3 – An object storage service for structured and unstructured data, S3 gives you the compute resources to build a data lake from scratch. Data transformation dbt – Short for data build tool, is the open source leader for transforming data once it’s loaded into your warehouse.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

AUGUST 31, 2023

In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process. Not long after data warehouses moved to the cloud, so too did data lakes (a place to transform and store unstructured data), giving data teams even greater flexibility when it comes to managing their data assets.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52