I am trying to access a schema from another database using db links. I am able to tnsping that machine without any trouble, but when I try to make connection in SQL prompt using db link I am getting this error:. Both databases are running the same version of Linux OS and the same Oracle database version.
Any help would be much appreciated. Hi, I am not able to connect db link via SQL prompt. I have configured network again on both source and target side. Still no use.
Did you create the link under the same ID as the ID using it? You didn't create public database link. I have also tried public link it got same error.
Hi Deepak, I have created dblink using tns alias. Can you please explain what tns entry hard coded that you meant? Hi purneet, thanks for reply.
I have checked my tnsnames. You can usually disable or change that if so, as you need to let through your defined or default port Also, can you check on the TNS log path defined in the listener parameter file to see if any network activity got into the DB server at all? As the previous poster stated, tnsping is a useful test, if you have set up the tnsnames. Some name 22k Followers. Tech Sign In Page. Forgot Password? Don't have an account? Sign up. Jeffrey Beckstrom. June 20, AM. Something went wrong on our end.
Please try again later. Iudith Mentzel. June 20, PM. Just my guess, Kevin. Kevin Lee. June 21, PM. Hi, could you create dblink with tns entry hard coded to the link?
I think it can help. Create database link Using 'tnsping entry of the target db'.Manage your account and access personalized content. Sign up for an Oracle Account. Access your cloud dashboard, manage orders, and more. Sign up for a free trial. Oracle Data Integrator is a comprehensive data integration platform that covers all data integration requirements: from high-volume, high-performance batch loads, to event-driven, trickle-feed integration processes, to SOA-enabled data services.
The Oracle Data Integrator system requirements and supported platforms can be found here. Please refer to the certification matrix. All features and types of the certified database version are supported. Which technologies does Oracle Data Integrator integrate with?
A list of the source and target technologies supported by Oracle Data Integrator is included in the Oracle Data Integrator system requirements and supported platforms. I want to get started with Oracle Data Integrator, is a demo environment provided? Where can I find a list of all the new features in this release?
Yes, it supports non-Oracle databases. Please refer to the certification matrix for more details. Please refer to the documentatio n for further details. Yes, it is strongly recommended because RCU creates the dependent schema types as well which are needed down the line for configuring the ODI Agent.
Yes, as long as the Fusion Middleware version is supported in the certification matrix. Why is this needed when the Enterprise install type itself includes Standalone Agent s? Yes, you would need to install the Standalone install type again in a separate Oracle home. Please refer to the Installation Guide to understand the difference among the various types of Agents. Can the configuration wizard launched from the Enterprise install location be used for configuring a Standalone Agent also?
To configure the Standalone Agent the configuration wizard should be launched from the Standalone installation location. The configuration wizard from the Enterprise install location can be used for configuring Collocated Standalone Agent s that get installed with the Enterprise install type.
The libraries required by the WebLogic Management Framework get laid down by the installer on selecting the Standalone install option. Standard Edition of WLS would be sufficient. JDK is required to run the installer.
Where can I find some information about the Oracle Data Integrator concepts and its architecture? If you are working with a version below After upgrading to Depending on your installation type, please refer to the Upgrade Guide for the upgrade path. Oracle Data Integrator 12c includes numerous product enhancements and capabilities. Oracle has invested in the following key areas in this release:.
Superior productivity with a new flow-based declarative user interface. The enhanced user experience is simple yet powerful and comprehensive; the ability to seamlessly reuse mapping logic speeds up development and overall time to solution. Where can I find more information about current customers and how they implemented Oracle Data Integrator?
The latest Oracle pricing and licensing information can be found in the Global Pricing and Licensing page on Oracle.This chapter describes how to set up the topology in Oracle Data Integrator. An overview of Oracle Data Integrator topology concepts and components is provided. The Oracle Data Integrator Topology is the physical and logical representation of the Oracle Data Integrator architecture and components.
Before you can perform the procedures described in this chapter, you must have installed and configured Oracle Data Integrator, database schemas, domains, and agents, as described in the Installation Guide for Oracle Data Integrator.
The Installation Guide uses the term "topology" in some sections to refer to the organization of servers, folders, and files on your physical servers. The physical architecture defines the different elements of the information system, as well as their characteristics taken into account by Oracle Data Integrator.
Each type of database Oracle, DB2, etc. A technology handles formatted data. Therefore, each technology is associated with one or more data types that allow Oracle Data Integrator to generate data handling scripts.
The physical components that store and expose structured data are defined as data servers. A data server is always linked to a single technology.
A data server stores information according to a specific technical logic which is declared into physical schemas attached to this data server. Every database server, JMS message file, group of flat files, and so forth, that is used in Oracle Data Integrator, must be declared as a data server.
Every schema, database, JMS Topic, etc. Finally, the physical architecture includes the definition of the Physical Agents. These are the Java software components that run Oracle Data Integrator jobs. Contexts bring together components of the physical architecture the real Architecture of the information system with components of the Oracle Data Integrator logical architecture the Architecture on which the user works.
For example, contexts may correspond to different execution environments DevelopmentTest and Production or different execution locations Boston SiteNew-York Siteand so forth. The logical architecture allows a user to identify as a single Logical Schema a group of similar physical schemas - that is containing datastores that are structurally identical - but located in different physical locations.
Logical Schemas, like their physical counterpart, are attached to a technology. Context allow to resolve logical schemas into physical schemas. In a given context, one logical schema resolves in a single physical schema. For example, the Oracle logical schema Accounting may correspond to two Oracle physical schemas:.
Accounting Sample used in the Development context. Accounting Corporate used in the Production context. These two physical schemas are structurally identical they contain accounting databut are located in different physical locations.
These locations are two different Oracle schemas Physical Schemaspossibly located on two different Oracle instances Data Servers.
All the components developed in Oracle Data Integrator are designed on top of the logical architecture. For example, a data model is always attached to logical schema, and data flows are defined with this model.
By specifying a context at run-time, the model's logical schema resolves to a single physical schema, and the data contained in this schema in the data server can be accessed by the integration processes.
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Oracle Data Integrator run-time Agents orchestrate the execution of jobs. These agents are Java components.The choice will depend on your goal, if you need to do a partial export then the Export Without Child Components is the one to use. The Export Multiple Objects feature is useful when you need to regularly export the same set of Objects.
Once the export has been performed, it is very important to choose the import strategy to suite your requirements. External reference IDs are not recalculated.
External references IDs are not recalculated. If an Object with the same ID exists in the Repository the import operation will not effect the numeric value it will not be replaced. Its properties and child components will be updated accordingly.
If an Object with the same ID does not exist in the new Repository, the import operation will have no effect. If the Object already exists, this method should be avoided when the export of the initial Object was performed without its child components.
This is to avoid any potential deletions of sub-components of the existing Object. Creates a new object in the target Repository and inserts into it all of the elements which are present in the.
The ID of this new object will be based on the ID of the Repository in which it is to be created the target Repository. Inserts a new object into the target Repository with the object ID as created in the original Source Repository ie the one stored in the XML export file being used for the import operation.
If any error is signaled, the transaction is aborted and an error message is displayed on standard output. Hence, this is potential way to corrupt the Scenario. Or in Duplication mode, but then this will create a new Scenario object, with a new internal ID — and this is may not be what you are attempting to do. So again, the Package is corrupted after import. Replaces the already existing ODI object in the target Repository with the one present in the XML file being used for the import operation.
This synonym import operation may even result in unexpected updates since there might already exist an object in the target Repository that has the same identical ID as the object stored in the XML file being used for the import operation.
This import mode inserts an object with the SAME attributes as those attached to the object present in the XML file being used for the import operation. If any of the incoming attributes violate any referential constraints, the operation is aborted and an error message is signaled in the standard output.
This will certainly occur when the Work Repository ID is identical to the one from which the export file has been created. You are commenting using your WordPress. You are commenting using your Google account.Learn what you can do with Oracle Data Integrator and understand the important concepts before you get started. Oracle Data Integrator ODI provides a fully unified solution for building, deploying, and managing complex data warehouses or as part of data- centric architectures in a SOA or business intelligence environment.
In addition, it combines all the elements of data integration - data movement, data synchronization, data quality, data management, and data services - to ensure that information is timely, accurate, and consistent across complex systems. Traditional ETL Extract, Transform, Load tools operate by, first, extracting the data from various sources, then, transforming the data in a proprietary, middle-tier ETL engine that is used as the staging area, and finally loading the transformed data into the target data warehouse, integration server, or Hadoop cluster.
Hence the term ETL represents both the names and the order of the operations performed. ODI extracts the data from the various sources, and then loads it to the target where it's transformed. ODI features an active integration platform that includes all styles of data integration: data-based, event-based and service-based. It also provides robust data integrity control features, assuring the consistency and correctness of data.
With powerful core differentiators - heterogeneous E-LT, Declarative Design and Knowledge Modules - ODI meets the performance, flexibility, productivity, modularity and hot-pluggability requirements of an integration platform. Objects developed or configured through the users are stored in one of these repository types. It's installed on an OLTP relational database. There's usually only one master repository that stores the Security information, Topology information, and versioned and archived objects.
The work repository is the one that contains actual developed objects. Several work repositories may coexist in the same ODI installation for example, to have separate environments or to match a particular versioning life cycle. A work repository stores information for Models, Projects, and Scenario execution. When the work repository contains only the execution information typically for production purposesit's called an execution repository. The Topology Navigator is used to manage the data describing the information system's physical and logical architecture.
Through it you can manage the topology of your information system, the technologies and their data types, the data servers linked to these technologies and the schemas they contain, the contexts, the language and the agents, as well as the repositories. The site, machine, and data server descriptions enable Oracle Data Integrator to execute the same mappings in different environments.
The Designer Navigator is used to design data integrity checks and to build transformations, such as automatic reverse-engineering of existing applications or databases, graphical development and maintenance of transformations and mappings, visualization of data flows in the mappings, automatic documentation generation, and customization of the generated code.
The main objects handled through it are Models and Projects. The Operator Navigator is the production management and monitoring tool.
It's designed for IT production operators. Through it you can manage your executions in the sessions, as well as the scenarios in production. Through it you can create users and profiles and assign user rights for methods on generic objects, and fine-tune these rights on the object instances.
At design time, developers generate scenarios from the business rules that they have designed. The code of these scenarios is then retrieved from the repository by the Run-Time Agent. This agent then connects to the data servers and orchestrates the code execution on these servers. It retrieves the return codes and messages for the execution, as well as additional logging information - such as the number of processed records, and execution time - in the repository.
The standalone agent is more appropriate when you need to use a resource that is local to one of your data servers, and you do not want to install a Java EE application server on this machine. Standalone colocated agents can be installed on any server with a Java Virtual Machine installed, but require a connection to the WebLogic Administration Server. This type of agent is more appropriate when you need to use a resource that is local to one of your data servers but you want to centralize management of all applications in an enterprise application server.
A Java EE agent is deployed as a web application in a Java EE application server, and can benefit from all the features of the application server. This type of agent is more appropriate when there is a need for centralizing the deployment and management of all applications in an enterprise application server, or when you have requirements for high availability.
Oracle Data Integrator Agents. The physical components that store and expose structured data in Oracle Data Integrator ODI are defined as data servers. Each data server is always linked to a single technology. It stores information according to a specific technical logic, which is declared in the physical schemas attached to it.I am unable to register because my data already exists on NaijaBet. What do I do? After registering can I still edit my profile data?
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It is strictly forbidden for persons under the age of 18 to open an account on NaijaBet and use our services. Yes No. Confirmation Do you really want to proceed? OK Close. Session Expired Please login again. Multiple sessions You have been signed out due to multiple logins. Please sign in again.In this case study we look at how, to reach new customers, UK leisure operator Everyone Active shares data about its available products and how to purchase them. This case study is part of a project exploring the value of data sharing in the private sector.
When sharing data, businesses face a range of challenges. A significant barrier is a lack of understanding of how increasing access to data can create business value, for example, by enabling new business models, increasing efficiency or reducing costs.
To help address this, we have been documenting real-world examples of how the private sector is creating value from increasing access to data. Many businesses are embracing the sharing of data, and are seeing tangible benefits for their organisations and across their entire sectors. Josh shares his top seven reasons why businesses should be sharing data. Read article.
The ODI is engaging with private-sector companies to show how sharing data can positively impact the bottom line. We are already seeing open approaches to data happening in sectors such as physical activity, banking, and pharmaceuticals.
This project seeks to demonstrate the business value of sharing data to a sector, network or individual business, looking at how an organisation might benefit in terms of innovation, network capabilities, and brand positioning. Find out more. Get in touch with our team to discuss the potential for your organisation to get more from data, join our events and follow our research.
In this case study we look at how the global agriculture business Syngenta publishes open data to help evidence its commitments to being a more trustworthy organisation in the agriculture sector.
A significant barrier is a lack of understanding of how increasing access to data can create business value, for example by enabling new business models, increasing efficiency or reducing costs. How can they do this so that it benefits themselves and others in the data ecosystem? In particular, how does this apply to data intermediaries — organisations who collect, validate or analyse data on behalf of customers?
Financial companies often make their investment decisions based on specific but widely available sources of data. Balance sheets, cash flow statements, press releases, quarterly reports and investor briefings would all be considered traditional forms of investment data. However, some companies have sought out new data sources to help inform their investment decisions. These datasets, often released by non-financial organisations, can help predict price-moving events that traditional data sources may miss, get wrong or not yet know about.
While there are many ways in which data and value are shared, a common scenario is the following. An organisation publishes data which a data provider will acquire and test to see if it contains useful investment signals. The data provider can then provide access to this repurposed data to a data intermediary who collects, validates and creates insights into data from many providers.
This intermediary will provide access to their collections of data and insights to data customers, who can then use this data to inform their investment decisions. Those using alt data must also consider legal and ethical implications. Many regions have strict legal guidelines regarding personal data processing.
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Organisations may acquire data that is labelled as anonymised data but in fact could identify individuals, especially when combined with datasets from different sources. For example, web scraping is routinely used to gather alt data but is a legal grey area which has led to several court cases.
Companies found in breach — or even considered to be in breach — of any of these laws can face serious financial and reputational consequences. Because of these risks, companies must be able to rely on and trust each other within an alt data ecosystem. The data customer must trust the data intermediary to sell safe data and in turn the intermediary must trust the data provider. The ODI has examined trustworthiness in alt data ecosystems in previous work with Refinitiv. We have found that organisations can assess, build and demonstrate their trustworthiness by using tools and mechanisms like contracts, audits, codes of ethics and certifications.
We have also found that sustainability relies on continued access to the data, a demand for that data, a viable business model around it, and maintaining working relationships. As part of this project, we will host online workshops and conduct interviews with Refinitiv and other experts in the alt data space. We believe that helping to guide the alt data sector towards better practices and standards can benefit all parties in alt data ecosystems and indeed wider society.
If you have thoughts or just want to hear more about the project, please drop us a line. Domestic regulators around the world that want to enable the use of data in modern technology face difficult choices in the regulation of combinatorial innovationbut at least benefit from guidance on approaches such as anticipatory regulation.