The document discusses key aspects of database management including making data sharable, consistent, and standardized across multiple departments and processes. It describes how a database management system (DBMS) is used to create, manage, and control access to the database. Examples are given of how DBMS can help with tasks like sales monitoring, marketing analysis, customer engagement, logistics management, employee records, financial planning, and more. Database design considerations involve determining tables and fields needed and relationships between tables.
Data Warehouse Process and Technology: Warehousing Strategy, Warehouse management and Support Processes.
Warehouse Planning and Implementation.
H/w and O.S. for Data Warehousing, C/Server Computing Model & Data Warehousing, Parallel Processors & Cluster Systems, Distributed DBMS implementations.
Warehousing Software, Warehouse Schema Design.
Data Extraction, Cleanup & Transformation Tools, Warehouse Metadata
,data warehouse process and technology: warehousing ,warehouse management and support processes. wareh ,c/server computing model & data warehousing ,parallel processors & cluster systems ,distributed dbms implementations. warehousing sof ,warehouse schema design. data extraction ,cleanup & transformation tools ,warehouse metadata
What is Data Warehouse?OLTP vs. OLAP, Conceptual Modeling of Data Warehouses,Data Warehousing Components, Data Warehousing Components, Building a Data Warehouse, Mapping the Data Warehouse to a Multiprocessor Architecture, Database Architectures for Parallel Processing
Data Warehouse Process and Technology: Warehousing Strategy, Warehouse management and Support Processes.
Warehouse Planning and Implementation.
H/w and O.S. for Data Warehousing, C/Server Computing Model & Data Warehousing, Parallel Processors & Cluster Systems, Distributed DBMS implementations.
Warehousing Software, Warehouse Schema Design.
Data Extraction, Cleanup & Transformation Tools, Warehouse Metadata
,data warehouse process and technology: warehousing ,warehouse management and support processes. wareh ,c/server computing model & data warehousing ,parallel processors & cluster systems ,distributed dbms implementations. warehousing sof ,warehouse schema design. data extraction ,cleanup & transformation tools ,warehouse metadata
What is Data Warehouse?OLTP vs. OLAP, Conceptual Modeling of Data Warehouses,Data Warehousing Components, Data Warehousing Components, Building a Data Warehouse, Mapping the Data Warehouse to a Multiprocessor Architecture, Database Architectures for Parallel Processing
Se presentan conceptos de Integración,influencia ,poder ,liderazgo, así como tambíen los tipos de liderazgo que se deben tomar en cuenta dentro de una empresa, y no olvidemos aquello0s factores de comunicación que permiten llevar una buena relación de trabajo.
Database Management allow person to organize, store and retrieve data from a computer. How database management contributes to achieving your business growth.
For more details visit: https://www.konverge.co.in/what-is-database-management/
Detailed slides of data resource management. The relationships among the many individual data elements stored in databases are based on one of several logical data structures, or models.
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In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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Send an interactive Slack channel message (using buttons)
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But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
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And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
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Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
2. • Sharable
- data that is being created at any one point in the organisation is of use for
multiple departments , processes or SBU’s, and should be easily sharable by
all the relevant departments , processes and SBU’s
•Consistent
- when dealing with multiple and completely independent data sources ,a
single fact might be stored at a number of places differently
• Reduced redundancy
- in file systems or application data stores , same data is often stored in
multiple places as well as a multiple number of times in the same data store
• Standardized
- representation of data should be in a standard form so that sharability of
data is possible
3. • Software used to create, manage and
control the database is called a database
management system (DBMS)
• Access and use of the data stored in the
database is only through the database
management system
4.
5. A DBMS can help in monitoring sales, summarize sales data,
inventory tracking and analysis, quick answers to ad-hoc
queries
A marketing database can support an enterprise- level
marketing analysis , demand forecasting and distribution
management, resulting in more effective processes.
Customer databases can help marketers to engage in selling
personalized products and services and also be used for target
marketing campaigns
A DBMS can support the logistics , distribution and
materials management process in a very effective manner by
linking the sales database to the inventory database for realtime inventory management
6. A database which contains the qualification and experience
details about employees can be extremely handy in job scheduling
on a daily or a weekly basis
A database management system can be used to store the
performance history of an employee and thus help in analyzing
the training needs of the employees
Online leave and attendance records in a database can be
extremely helpful in analyzing certain employee behaviors and
thus help the HR managers to find a solution to this problem
An HR DBMS can help in performance evaluation and benefits
administration on a real-time basis without employees having to
write letters and letters for benefits claim
Knowledge databases can support the organizational learning
model
7. The data required for evaluation and creation of financial and economic
forecasting, budget and investment planning is available in financial
databases
A DBMS system provides a facility for validation by means of validation
checks , controls and constraints.
Using a knowledge base of financial data can help in financial and
economic forecasting which is otherwise a very lengthy and tedious
procedure.
DBMS system can support an online bill and invoicing procedure and link
it with the delivery and receipt of products
8. Determine the purpose of your database
Determine the tables you need in the
database
Determine the fields you need in the
tables
Identify fields with unique values
Determine
tables
the
relationships
between
9. Represents the language of the organisation
(processes of the organisation)
Represents the fundamental structure of the
organisation
(information
processing
requirements of each process and the information
links between various processes)
Represents the physical structure of the
database (logical and physical schemas of the data
store)
10.
11. Databases stored on multiple computers
that typically appears to applications as a
single database
Thus an application can simultaneously
access and modify the data in several
databases in a network
Databases are connected via a network,
either local a are or wide area, which may
involve different database management
systems, running on different architectures,
that distributes the execution of transactions
12.
13. •A data warehouse is a single,
centralized, enterprise-wide repository
which combined all the data from all
legacy systems and theoretically gave all
users access to appropriate information
14.
15. • The data for the data warehouse is first extracted
from its native sources, such as OLTP ( Online
Transaction Processing System) databases, text files,
Microsoft Access, and even spreadsheets and various
operational sources
• This data is then placed in a data warehouse that has a
structure compatible with data model
• The data stored in the data warehouse resides in the
form of facts and dimensions