Cloudera

SEPTEMBER 7, 2018

Enterprises prepare to avoid or tackle threats by monitoring employee and third-party communications such as e-mail, instant messaging, social media, and voice, as well as by analyzing log files and file attachments. Moreover, this approach struggles to deal with the large volume and variety of data that must be analyzed and often correlated.

Machine Learning 49

Machine Learning Unstructured Data Portfolio Relational Database 49

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. Similarly, you can pull information from social media.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

APRIL 3, 2023

There are several types of databases, including relational, NoSQL, object-oriented, hierarchical, network, and graph databases. Relational databases use a tabular structure to organize data, while NoSQL databases are designed to handle large volumes of unstructured data.

Programming Language 52

Programming Language Computer Science Portfolio PostgreSQL 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

JULY 13, 2015

Apache Hadoop is the framework of choice for JPMorgan - not only to support the exponentially growing data size but more importantly for the fast processing of complex unstructured data. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

SEPTEMBER 26, 2014

BI professionals use various tools to draw useful data that are used to generate customized reports and this is where the Hadoop File Distribution System (HDFS) proves itself. When it comes to processing massive amounts of data, scaling of traditional RDBMS's proves extremely expensive. These files can be saved on Hadoop HDFS.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

ProjectPro

NOVEMBER 14, 2015

Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data. This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. Hadoop came as a rescue when the data volume coming from different sources increased exponentially.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

FEBRUARY 21, 2023

Microsoft introduced the Data Engineering on Microsoft Azure DP 203 certification exam in June 2021 to replace the earlier two exams. This professional certificate demonstrates one's abilities to integrate, analyze, and transform various structured and unstructured data for creating effective data analytics solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 6, 2015

“Solocal is a company that Yellow Media had always admired in terms of their ability to grow their online audiences.”-said Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization So what are the pains of the BI? This is implemented at Solocal.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JULY 24, 2023

According to recent studies, the global database market will grow from USD 63.4 SQL is a powerful tool for managing and manipulating relational databases, and it continues to be widely used in the industry today. One of its most significant benefits is its ability to quickly process a vast amount of data.

SQL 52

SQL Database Process NoSQL 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

Knowledge Hut

DECEMBER 26, 2023

Analyzing more data points will therefore give you a more detailed insight into your study. The spectrum of sources from which data is collected for the study in Data Science is broad. It comes from numerous sources ranging from surveys, social media platforms, e-commerce websites, browsing searches, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

MARCH 19, 2024

Relational Database Service (RDS) Use Cases Since Amazon Relational Database Service (Amazon RDS) is a managed database service, it alleviates the stress associated with maintaining, administering, and other database-related responsibilities.

AWS 52

AWS Amazon Web Services Hospitality Cloud Computing 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

ProjectPro

OCTOBER 28, 2015

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

OCTOBER 3, 2022

Bringing data together from heterogeneous enterprise sources and creating a unified view of that data is a popular application of knowledge graphs. This is especially useful for big enterprises when the sources are presented in different formats (CSV, XML, JSON, relational databases) and use different data schemas.

Relational Database 52

Relational Database Banking Media Computer Science 52

Edureka

FEBRUARY 9, 2023

Its high scalability, fault tolerance, and simplicity make the framework a popular option for big data processing and analytics. Organizations frequently use Hadoop to store and analyse big data from a variety of sources, including social media, internet of things (IoT) devices, and log files.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

FEBRUARY 8, 2023

This serverless data integration service can automatically and quickly discover structured or unstructured enterprise data when stored in data lakes in Amazon S3, data warehouses in Amazon Redshift, and other databases that are a component of the Amazon Relational Database Service.

AWS 98

AWS Scala Metadata Data Lake 98

U-Next

AUGUST 25, 2022

Is MongoDB A Relational Database? Similar to columns in a relational database, fields in texts are crucial combinations. Any BSON data type, including integer, boolean, and others, may be used as a value for a field. We can store layered data in MongoDB objects.

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

AltexSoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc.

Big Data 78

Big Data Data Analytics IT NoSQL 78

U-Next

SEPTEMBER 9, 2022

The platform distributes Hadoop large data and analytics operations among computer cluster nodes, breaking them down into smaller workloads that may be handled in parallel. Hadoop can scale up from a single server to thousands of servers and analyze organized and unstructured data. . What is Hadoop in Big Data? .

Hadoop 40

Hadoop Big Data Management Unstructured Data 40

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

U-Next

AUGUST 3, 2022

A high-ranking expert is known as a “Data Scientist” who works with big data and has the mathematics, economic, technical, analytic, and technological abilities necessary to cleanse, analyse and evaluate organised and unstructured data to help organisations make more informed decisions.

Retail 52

Retail Data Science Computer Science Entertainment 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

AltexSoft

NOVEMBER 10, 2021

Prior to the recent advances in data management technologies, there were two main types of data stores companies could make use of, namely data warehouses and data lakes. Data warehouse. Inability to handle unstructured data such as audio, video, text documents, and social media posts.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

NOVEMBER 23, 2021

Nowadays, all organizations need real-time data to make instant business decisions and bring value to their customers faster. But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Data virtualization architecture example.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

AUGUST 11, 2021

Any inconsistencies found in the data are removed, and all gaps that can be filled are filled to ensure that the data maintains integrity. Data Warehouse Layer: Once the data is transformed into the required format, it is saved into a central repository.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

AUGUST 26, 2015

1997 -The term “BIG DATA” was used for the first time- A paper on Visualization published by David Ellsworth and Michael Cox of NASA’s Ames Research Centre mentioned about the challenges in working with large unstructured data sets with the existing computing systems. Truskowski.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

ProjectPro

JULY 30, 2021

Use cases are in-memory caches and open-source databases. They are used ideally for media transcoding, gaming servers, ad-server engines. It backs up data in AWS S3 in real-time without any performance impact. It backs up storage in a routine fashion without the hassle of Database administrators interfering.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

Knowledge Hut

JANUARY 11, 2024

Data Science can be described as a domain that applies advanced analytics, statistics and scientific principle for extracting valuable information and deriving valuable conclusions from structured or unstructured data. Terms like Machine Learning and Artificial Intelligence are often used in data science.

Finance 93

Finance Data Science Programming Language Machine Learning 93

Knowledge Hut

DECEMBER 26, 2023

Some of these ideas consist of: Big data technology and technologists deal with a number of similar problems, such as data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns. Relational and non-relational databases, such as RDBMS, NoSQL, and NewSQL databases.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

U-Next

SEPTEMBER 23, 2022

Previously, organizations dealt with static, centrally stored data collected from numerous sources, but with the advent of the web and cloud services, cloud computing is fast supplanting the traditional in-house system as a dependable, scalable, and cost-effective IT solution. The ingestion layer is the initial step in bringing in raw data.

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

MAY 31, 2021

And even if you’re not very active on social media, I’m sure you now and then check your phone before leaving the house to see what the traffic is like on your route to know how long it could take you to reach your destination. Spark has a Streaming tool that can process real-time streaming data.

Big Data 52

Big Data Coding Project Hadoop 52

Knowledge Hut

FEBRUARY 28, 2024

In this blog, we will explore the future of big data in business, its applications, and the technologies that will drive its evolution. What is Big Data? Big data refers to large amounts of data. The differentiation between data and big data becomes clear once we look at the methods of analyzing them.

Big Data 52

Big Data Cloud Storage Healthcare SQL 52

U-Next

SEPTEMBER 29, 2022

In order to make informed decisions, organizations need to leverage data. . Types of Data in an Organization . A structured data record consists of a very fixed field of data. Relational databases, spreadsheets, and other documents can contain this type of data. Cultural Dynamics .

Management 52

Management Unstructured Data Data Government 52