Oracle Data Integrator is an ELT data integrator designed with interoperability other Oracle programs. The program focuses on a high-performance capacity to support Big Data use within Oracle.
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Oracle Utilities Meter Data Management (MDM)
Score 9.0 out of 10
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Oracle supplies a suite of utilities management applications, including the Oracle Utilities Meter Data Management (MDM) application.
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Pricing
Oracle Data Integrator (ODI)
Oracle Utilities Meter Data Management (MDM)
Editions & Modules
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Offerings
Pricing Offerings
Oracle Data Integrator (ODI)
Oracle Utilities Meter Data Management (MDM)
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Oracle Data Integrator (ODI)
Oracle Utilities Meter Data Management (MDM)
Features
Oracle Data Integrator (ODI)
Oracle Utilities Meter Data Management (MDM)
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Oracle Data Integrator (ODI)
8.0
12 Ratings
3% below category average
Oracle Utilities Meter Data Management (MDM)
-
Ratings
Connect to traditional data sources
8.012 Ratings
00 Ratings
Connecto to Big Data and NoSQL
8.010 Ratings
00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Oracle Data Integrator (ODI)
8.0
12 Ratings
0% below category average
Oracle Utilities Meter Data Management (MDM)
-
Ratings
Simple transformations
8.012 Ratings
00 Ratings
Complex transformations
8.012 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Oracle Data Integrator (ODI)
7.4
12 Ratings
5% below category average
Oracle Utilities Meter Data Management (MDM)
-
Ratings
Data model creation
8.011 Ratings
00 Ratings
Metadata management
8.011 Ratings
00 Ratings
Business rules and workflow
7.012 Ratings
00 Ratings
Collaboration
7.011 Ratings
00 Ratings
Testing and debugging
7.012 Ratings
00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Oracle Data Integrator is well suited in all the situations where you need to integrate data from and to different systems/technologies/environments or to schedule some tasks. I've used it on Oracle Database (Data Warehouses or Data Marts), with great loading and transforming performances to accomplish any kind of relational task. This is true for all Oracle applications (like Hyperion Planning, Hyperion Essbase, Hyperion Financial Management, and so on). I've also used it to manage files on different operating systems, to execute procedures in various languages and to read and write data from and to non-Oracle technologies, and I can confirm that its performances have always been very good. It can become less appropriate depending on the expenses that can be afforded by the customer since its license costs are quite high.
Oracle Utilities MDM is well suited for users that have plenty of money to invest in technical hardware resources to support the requirements of this application. With the electric utility industry becoming more and more precise data-wise, the requirements for data storage and processing are only going to increase. For example, electrical usage measurement used to be a once-a-month practice; in the 1990s, hourly reading was introduced; recently, 15-minute interval readings have been introduced and will become the new norm. Going from one reading a month, to 720, to now 2,880 requires expensive hardware. MDM is able to handle this load, in our experience, only if you purchase Oracle's Exadata hardware, which is priced at a premium. Beyond data storage itself, we have also found that MDM real-time usage for users is also, unfortunately, best with Exadata. Likely because Oracle developed this hardware, and because it has built-in compression, portioning, and tuning features, performance is better. One note is that Oracle does provide a purge-and-archive strategy in the more recent versions of MDM (i.e. ILM). However, implementation of this is a small project in itself, although worthwhile in the long run.
Oracle Data Integrator nearly addresses every data issue that one can expect. Oracle Data Integrator is tightly integrated to the Oracle Suite of products. This is one of the major strengths of Oracle Data Integrator. Oracle Data Integrator is part of the Oracle Business Intelligence Applications Suite - which is highly used by various industries. This tool replaced Informatica ETL in Oracle Business Intelligence Applications Suite.
Oracle Data Integrator comes with many pre-written data packages. If one has to load data from Excel to Oracle Database, there is a package that is ready available for them - cutting down lot of effort on writing the code. Similarly, there are packages for Oracle to SQL, SQL to Oracle and all other possible combinations. Developers love this feature.
Oracle Data Integrator relies highly on the database for processing. This is actually an ELT tool rather than an ETL tool. It first loads all the data into target instance and then transforms it at the expense of database resources. This light footprint makes this tool very special.
The other major advantage of Oracle Data Integrator, like any other Oracle products, is a readily available developer pool. As all Oracle products are free to download for demo environments, many organizations prefer to play around with a product before purchasing it. Also, Oracle support and community is a big advantage compared to other vendors.
ODI does not have an intuitive user interface. It is powerful, but difficult to figure out at first. There is a significant learning curve between usability, proficiency, and mastery of the tool.
ODI contains some frustrating bugs. It is Java based and has some caching issues, often requiring you to restart the program before you see your code changes stick.
ODI does not have a strong versioning process. It is not intuitive to keep an up to date repository of versioned code packages. This can create versioning issues between environments if you do not have a strong external code versioning process.
In some ways, MDM is too customizable. There is a delicate balance to be struck between allowing implementers the ability to create custom algorithms to meet their business needs and making those features part of the base product. Lots of things can go wrong if you customize it too much.
It is maturing and over time will have a good pool of resources. Each new version has addressed the issues of the previous ones. Its getting better and bigger.
Oracle Data Integrator (ODI) is a reliable ELT tool, supporting data loads from various heterogenous sources. It is effective both for structured as well as non structured data. Its works well for creating translations and transformation and also aids in the data quality checks when combined with an MDM solution. Troubleshooting issues can be of a challenge if it is not configured properly.
I have used Trifacta Google Data Prep quite a bit. We use Google Cloud Platform across our organization. The tools are very comparable in what they offer. I would say Data Prep has a slight edge in usability and a cleaner UI, but both of the tools have comparable toolsets.
Although I have minimal experience with meter data management products outside of MDM, it does perform better than an in-house product developed by our utility 20 years ago for use on our mainframe-based system then. Meter management is headed the same way as other industries in terms of data usage and mining. The requirement for data is only going to continue to increase, and at this time it appears that MDM is only just keeping up with those requirements. Oracle has done a great job of purchasing products and integrating them into their overall framework, but the current database structure of MDM lends itself to poor performance if Oracle's own hardware is not purchased, and if their purge and archive strategy (i.e. ILM) is not employed.
Preventing errors for us always turns into money saved. Error flags that MDM throws help to prevent incorrect data entry, which almost always turns into money and time spent on sending somebody out into the field to ensure accurate data was given. So by not allowing for the possible errors, we save money.