Knowledge Hut

JANUARY 19, 2024

Business Intelligence Transforming raw data into actionable insights for informed business decisions. This subject equips you with skills in handling various BI (Business Intelligence) methods and tools. Reducing the burden of managing physical hardware. "The Art of Data Science" Roger D.

Data Science 52

Data Science Machine Learning Datasets Algorithm 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? This statistic probably comes as no surprise.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

AltexSoft

MARCH 28, 2022

The data also indicates that more and more companies in the sector tie their bright future with… data. According to the Global Vacation Rental Report 2022 , 40 percent of property managers rely on market business intelligence (BI) or analytics services, a big leap compared to just 13 percent before the COVID-19 outbreak.

Hospitality 52

Hospitality Business Intelligence Datasets Machine Learning 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineer Salary by Experience (Entry-Level, Mid-Level, and Senior) Entry-Level Big Data Engineer Salary An entry-level position does not demand years of experience in Big Data technology. However, one should have an educational background and theoretical knowledge in data management.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. ETL is the acronym for Extract, Transform, and Load.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

SEPTEMBER 30, 2014

Reason Three: Handle Unstructured Data As organizations across all industries continue growing at breakneck pace, they generate high volume, complex and unstructured data which are exposing the limitations of the traditional ETL systems.

Hadoop 52

Hadoop Unstructured Data ETL Tools ETL System 52

Knowledge Hut

SEPTEMBER 26, 2023

The demand for data professionals with business intelligence skills has increased significantly in recent years. With technological advancements and digital transformations, businesses are taking data very seriously. In today's business environment, data is an invaluable asset.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

ProjectPro

MAY 20, 2015

CRN editorial team, has appreciated this challenge taken up by various big data companies and identified the best big data and business analytics companies that are innovating out-of-the-box data management, business analytics and infrastructure services and technologies in the big data market.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

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

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure's Azure Synapse, formerly known as Azure SQL Data Warehouse, is a complete analytics offering. Designed to tackle the challenges of modern data management and analytics, Azure Synapse brings together the worlds of big data and data warehousing into a unified and seamlessly integrated platform.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Edureka

AUGUST 2, 2023

Their efforts make ensuring that data is accurate, dependable, and consistent, laying the groundwork for data analysis and decision-making. What does a Data Processing Analysts do ? A data processing analyst’s job description includes a variety of duties that are essential to efficient data management.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

ProjectPro

JANUARY 27, 2023

If you're wondering how the ETL process can drive your company to a new era of success, this blog will help you discover what use cases of ETL make it a critical component in many data management and analytic systems. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 52

BI ETL Tools Retail Healthcare 52

U-Next

OCTOBER 25, 2022

What Is Data Manipulation? . In data manipulation, data is organized in a way that makes it easier to read, or that makes it more visually appealing, or that makes it more structured. Data collections can be organized alphabetically to make them easier to understand. . within an organization. .

Business Intelligence 40

Business Intelligence Raw Data Data Cleanse Data Analysis 40

Knowledge Hut

DECEMBER 29, 2023

The highlight feature of this platform is its potential to integrate semi-structured and structured data without using any third-party tools. Snowflake also has an automatic query optimization system, so you wouldn’t have to worry about managing its settings.

Data Engineering 40

Data Engineering Data Engineer Engineering BI 40

AltexSoft

NOVEMBER 10, 2021

Well, there’s a new phenomenon in data management that received the name of a data lakehouse. 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. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

JANUARY 31, 2022

Snowflake Features that Make Data Science Easier Building Data Applications with Snowflake Data Warehouse Snowflake Data Warehouse Architecture How Does Snowflake Store Data Internally? This is the reason why we need Data Warehouses. What is Snowflake Data Warehouse?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

JULY 18, 2023

Spark SQL brings native support for SQL to Spark and streamlines the process of querying semistructured and structured data. It incorporates a comprehensive set of libraries, including Spark SQL for structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.

Big Data 52

Big Data Data Process Process Hadoop 52

AltexSoft

OCTOBER 8, 2021

The bad news is, integrating data can become a tedious task, especially when done manually. Luckily, there are various data integration tools that support automation and provide a unified data view for more efficient data management. Data integration process. Xplenty interface showing table-level components.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

AltexSoft

JULY 29, 2022

Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Scalability.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

SEPTEMBER 10, 2021

So, why does anyone need to integrate data in the first place? Today, companies want their business decisions to be driven by data. But here’s the thing — information required for business intelligence (BI) and analytics processes often lives in a breadth of databases and applications. Middleware data integration.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. What is Big Data analytics?

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 31, 2023

Define Big Data and Explain the Seven Vs of Big Data. Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. RDBMS stores structured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

DECEMBER 26, 2023

Big Data is an immense amount of data that is constantly growing exponentially. Due to its vastness and complexity, no traditional data management system can adequately store or process this data. The New York Stock Exchange, which generates one terabyte of new trade data each day, is a classic example of big data.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

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

Knowledge Hut

DECEMBER 13, 2023

Change is a constant, whether it be in the form of new businesses, products, processes, or approaches. Big Data startups compete for market share with the blue-chip giants that dominate the business intelligence software market. The top Data Analytics companies to take into account are listed below.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

phData: Data Engineering

JULY 18, 2023

To truly understand its potential, we need to explore the benefits it brings, particularly when transitioning from traditional data management structures. Why Migrate to a Modern Data Stack? Its spreadsheet-based interface makes high-level summaries and granular analyses easily accessible to all members of the business.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52