A data warehouse is a centralized repository that stores data from multiple information sources and transforms them into a common, multidimensional data model for efficient querying and analysis. Business intelligence systems use data warehouses to help with planning, problem solving, and decision support by providing multi-dimensional views of business activities and processes. ETL (extract, transform, load) is the process of pulling data out of source systems, transforming it if needed, and loading it into a data warehouse to support business intelligence applications and analysis.
this is the ppt this contains definition of data ware house , data , ware house, data modeling , data warehouse architecture and its type , data warehouse types, single tire, two tire, three tire .
Application of Data Warehousing & Data Mining to Exploitation for Supporting ...Gihan Wikramanayake
M G N A S Fernando, G N Wikramanayake (2004) "Application of Data Warehousing and Data Mining to Exploitation for Supporting the Planning of Higher Education System in Sri Lanka", In:23rd National Information Technology Conference, pp. 114-120. Computer Society of Sri Lanka Colombo, Sri Lanka: CSSL Jul 8-9, ISBN: 955-9155-12-1
Difference between data warehouse and data miningmaxonlinetr
What exactly is a Data Warehouse?
Termed as a special type of database, a Data Warehouse is used for storing large amounts of data, such as analytics, historical, or customer data, which can be leveraged to build large reports and also ensure data mining against it.@ http://maxonlinetraining.com/why-is-data-warehousing-online-training-important/
What is Data mining?
The process of extracting valid, previously unknown, comprehensible and actionable information from large databases and using it to make crucial business decisions’
Call us at For any queries, please contact:
+1 940 440 8084 / +91 953 383 7156 TODAY to join our Online IT Training course & find out how Max Online Training.com can help you embark on an exciting and lucrative IT career.
TODAY to join our Online IT Training course & find out how Max Online Training.com can help you embark on an exciting and lucrative IT career.
Visit www.maxonlinetraining.com
For Complete Course Overview and to a book @https://goo.gl/QbTVal
This document is about Data Warehouse Tools such as:
OLAP (On – line Analytical Processing)
OLTP (On – Line Transaction Processing)
Business Intelligence
Driving Force
Data Mart
Meta Data
this is the ppt this contains definition of data ware house , data , ware house, data modeling , data warehouse architecture and its type , data warehouse types, single tire, two tire, three tire .
Application of Data Warehousing & Data Mining to Exploitation for Supporting ...Gihan Wikramanayake
M G N A S Fernando, G N Wikramanayake (2004) "Application of Data Warehousing and Data Mining to Exploitation for Supporting the Planning of Higher Education System in Sri Lanka", In:23rd National Information Technology Conference, pp. 114-120. Computer Society of Sri Lanka Colombo, Sri Lanka: CSSL Jul 8-9, ISBN: 955-9155-12-1
Difference between data warehouse and data miningmaxonlinetr
What exactly is a Data Warehouse?
Termed as a special type of database, a Data Warehouse is used for storing large amounts of data, such as analytics, historical, or customer data, which can be leveraged to build large reports and also ensure data mining against it.@ http://maxonlinetraining.com/why-is-data-warehousing-online-training-important/
What is Data mining?
The process of extracting valid, previously unknown, comprehensible and actionable information from large databases and using it to make crucial business decisions’
Call us at For any queries, please contact:
+1 940 440 8084 / +91 953 383 7156 TODAY to join our Online IT Training course & find out how Max Online Training.com can help you embark on an exciting and lucrative IT career.
TODAY to join our Online IT Training course & find out how Max Online Training.com can help you embark on an exciting and lucrative IT career.
Visit www.maxonlinetraining.com
For Complete Course Overview and to a book @https://goo.gl/QbTVal
This document is about Data Warehouse Tools such as:
OLAP (On – line Analytical Processing)
OLTP (On – Line Transaction Processing)
Business Intelligence
Driving Force
Data Mart
Meta Data
A Computer database is a collection of logically related data that is stored in a computer system,so that a computer program or person using a query language can use it to answer queries. An operational database (OLTP) contains up-to-date, modifiable application specific data. A data warehouse (OLAP) is a subject-oriented, integrated, time-variant and non-volatile collection of data used to make business decisions. Hadoop Distributed File System (HDFS) allows storing large amount of data on a cloud of
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State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
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Major cyber events in 2024
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Attacks on counties – USA
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Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
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https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
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Bob Boule
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GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
us it recruiter
1. 1. DataWarehouse
Data Warehouse Architecture
Data Warehouse definition
A data warehouse isa:
1. subject-oriented
2. integrated
3. timevarying
4. Non-volatile collectionof datainsupportof the management'sdecision-makingprocess.
A data warehouse isacentralizedrepositorythatstoresdatafrommultiple informationsourcesand
transformsthemintoa common,multidimensional datamodel forefficientqueryingandanalysis.
2. OLTP vs. OLAP
We can divide ITsystemsintotransactional (OLTP) andanalytical(OLAP).Ingeneral we canassume that
OLTP systemsprovide source datatodata warehouses,whereasOLAPsystemshelptoanalyze it.
2. - OLTP (On-line Transaction Processing) ischaracterizedbya large numberof shorton-line transactions
(INSERT,UPDATE,DELETE). The mainemphasisforOLTP systemsisputon veryfastqueryprocessing,
maintainingdataintegrityinmulti-accessenvironmentsandaneffectivenessmeasuredbynumberof
transactionspersecond.InOLTP database there isdetailedandcurrentdata,and schemausedtostore
transactional databasesisthe entitymodel (usually3NF).
- OLAP (On-line Analytical Processing) ischaracterizedbyrelativelylow volume of transactions.Queries
are oftenverycomplex andinvolve aggregations.ForOLAPsystemsaresponse time isaneffectiveness
measure.OLAPapplicationsare widelyusedbyDataMiningtechniques.InOLAPdatabase there is
aggregated,historical data,storedinmulti-dimensional schemas(usuallystarschema).
The followingtable summarizesthe majordifferencesbetweenOLTPandOLAPsystemdesign.
OLTP System
Online Transaction Processing
(Operational System)
OLAP System
Online Analytical Processing
(Data Warehouse)
Source of data
Operational data; OLTPs are the original
source of the data.
Consolidation data; OLAP data comes from
the various OLTP Databases
Purpose of
data
To control and run fundamental
business tasks
To help with planning, problem solving, and
decision support
What the data
Reveals a snapshot of ongoing business
processes
Multi-dimensional views of various kinds of
business activities
Inserts and Short and fast inserts and updates Periodic long-running batch jobs refresh the
3. Updates initiated by end users data
Queries
Relatively standardized and simple
queries Returningrelatively few records
Oftencomplex queriesinvolving aggregations
Processing
Speed
Typically very fast
Depends on the amount of data involved;
batch data refreshesandcomplexqueriesmay
take many hours; query speed can be
improved by creating indexes
Space
Requirements
Can be relatively small if historical data
is archived
Larger due to the existence of aggregation
structures and history data; requires more
indexes than OLTP
Database
Design
Highly normalized with many tables
Typicallyde-normalizedwithfewertables;use
of star and/or snowflake schemas
Backup and
Recovery
Backup religiously; operational data is
critical to run the business, data loss is
likelytoentail significant monetary loss
and legal liability
Instead of regular backups, some
environments may consider simply reloading
the OLTP data as a recovery method
3. What is BusinessIntelligence?
BusinessIntelligence (BI) - technologyinfrastructure forgainingmaximuminformationfromavailable
data for the purpose of improvingbusinessprocesses.Typical BIinfrastructure componentsare as
follows:softwaresolutionforgathering,cleansing,integrating,analyzingandsharingdata.Business
Intelligenceproducesanalysisandprovidesbelievable informationtohelpmakingeffectiveandhigh
qualitybusinessdecisions.
The most commonkindsof BusinessIntelligence systemsare:
EIS - Executive InformationSystems
DSS - DecisionSupportSystems
MIS - ManagementInformationSystems
GIS - GeographicInformationSystems
OLAP - Online Analytical Processingandmultidimensional analysis
CRM - CustomerRelationshipManagement
BusinessIntelligence systemsbasedonDataWarehouse technology.A DataWarehouse(DW) gathers
informationfromawide range of company'soperational systems,BusinessIntelligence systemsbased
on it.Data loadedto DW isusuallygoodintegratedandcleanedthatallowstoproduce credible
information whichreflectedsocalled'one versionof the true'.
4. BusinessIntelligence tools
4. The most popularBI toolsonthe marketare:
Oracle - Siebel BusinessAnalyticsApplications
SAS- BusinessIntelligence
SAP - BusinessObjectsXI
IBM - Cognos8 BI
Oracle - HyperionSystem9BI+
Microsoft- AnalysisServices
MicroStrategy - DynamicEnterprise Dashboards
Pentaho- OpenBI Suite
InformationBuilders - WebFOCUSBusinessIntelligence
QlikTech- QlikView
TIBCO Spotfire - Enterprise Analytics
Sybase - InfoMaker
KXEN - IOLAP
SPSS– ShowCase
5. ETL tools
List of the most popularETL tools:
Informatica- PowerCenter
IBM - WebSphere DataStage(FormerlyknownasAscential DataStage)
SAP - BusinessObjectsDataIntegrator
IBM - CognosData Manager (FormerlyknownasCognosDecisionStream)
Microsoft- SQL ServerIntegrationServices
Oracle - Data Integrator(FormerlyknownasSunopsisDataConductor)
SAS- Data IntegrationStudio
Oracle - Warehouse Builder
AB Initio
InformationBuilders - DataMigrator
Pentaho- PentahoData Integration
EmbarcaderoTechnologies - DT/Studio
IKAN - ETL4ALL
IBM - DB2 Warehouse Edition
Pervasive - DataIntegrator
ETL SolutionsLtd. - TransformationManager
Group 1 Software (Sagent) - DataFlow
Sybase - Data IntegratedSuite ETL
Talend- TalendOpenStudio
ExpressorSoftware - ExpressorSemanticDataIntegrationSystem
Elixir- ElixirRepertoire
OpenSys - CloverETL
5. 6. ETL process
ETL (Extract, Transform and Load) is a processindata warehousingresponsibleforpullingdataoutof
the source systemsandplacingitinto a data warehouse.ETLinvolvesthe followingtasks:
- Extracting The Data from source systems(SAP,ERP,otheroprational systems),datafromdifferent
source systemsisconvertedintoone consolidateddatawarehouse formatwhichisreadyfor
transformationprocessing.
- Transforming The Data mayinvolve the followingtasks:
applyingbusinessrules(so-calledderivations,e.g.,calculatingnew measuresanddimensions),
cleaning(e.g.,mappingNULLto 0 or "Male"to "M" and "Female"to"F"etc.),
filtering(e.g.,selectingonlycertaincolumnstoload),
splittingacolumnintomultiplecolumnsandvice versa,
joiningtogetherdatafrommultiple sources(e.g.,lookup,merge),
transposingrowsandcolumns,
applyinganykindof simple orcomplex datavalidation(e.g.,if the first3columnsina row are
emptythenrejectthe rowfrom processing)
- Loading The Data intoa data warehouse ordata repositoryotherreportingapplications