Knowledge Hut

APRIL 25, 2024

As businesses increasingly rely on intangible assets to create value, an efficient data management strategy is more important than ever. Data Integration Data integration is the process of combining information from several sources to give people a cohesive perspective.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Monte Carlo

AUGUST 25, 2023

With pre-built functionalities and robust SQL support, data warehouses are tailor-made to enable swift, actionable querying for data analytics teams working primarily with structured data. This is particularly useful to data scientists and engineers as it provides more control over their calculations. Or maybe both.)

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

The Modern Data Company

MAY 10, 2023

Integration with existing systems: Ensure the solution can integrate seamlessly with your existing tools, applications, and infrastructure. Data governance and security: Evaluate the native security, data governance, and data quality management features. Needs to maintain data consistency and quality.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Integration with existing systems: Ensure the solution can integrate seamlessly with your existing tools, applications, and infrastructure. Data governance and security: Evaluate the native security, data governance, and data quality management features. Needs to maintain data consistency and quality.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Integration with existing systems: Ensure the solution can integrate seamlessly with your existing tools, applications, and infrastructure. Data governance and security: Evaluate the native security, data governance, and data quality management features. Needs to maintain data consistency and quality.

Data Management 52

Data Management Data Lake Management Data Warehouse 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

Databand.ai

JULY 19, 2023

The extracted data is often raw and unstructured and may come in various formats such as text, images, audio, or video. The extraction process requires careful planning to ensure data integrity. Often, the extraction process includes checks and balances to verify the accuracy and completeness of the extracted data.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

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

AltexSoft

SEPTEMBER 23, 2021

A data hub is a central mediation point between various data sources and data consumers. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. An ETL approach in the DW is considered slow, as it ships data in portions (batches.)

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. Integrate.io

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 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

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

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

Knowledge Hut

DECEMBER 29, 2023

Types of Specializations in Data Science (Areas of Data Science) The fields of business, research, and government are all increasingly using data science. 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

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 11, 2021

The data captured by a data lake does not necessarily have to be of immediate use but may be stored in the data lake for future use. Since vast amounts of data is present in a data lake, it is ideal for tracking analytical performance and data integration.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

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

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation. How Big Data Works?

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

JUNE 24, 2021

Data Cleaning: To improve the data quality and filter the noisy, inaccurate, and irrelevant data for analysis, data cleaning is a key skill needed for all analytics job roles. Microsoft Excel: A successful Excel spreadsheet helps to organize raw data into a more readable format.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

MAY 20, 2015

Several big data companies are looking to tame the zettabyte’s of BIG big data with analytics solutions that will help their customers turn it all in meaningful insights. Palantir Metropolis- This product focusses on information management, data integration and quantitative analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40