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OracleOracle Data Warehouse is a safe but good choice for in-house clinical data warehouse2018-08-07T16:08:05.410ZMy company is a non-profit organization of a healthcare system. We adopted Oracle Data Warehouse for building a clinical data warehouse, to support quality improvement and clinical research. Our hospitals and clinics run electronic health record systems that capture clinical data through patient care; the Data Warehouse is used to store them in a permanent manner. Once stored, the data can be normalized and standardized to be used by clinical departments, clinical champions, and researchers. There were a number of use cases in the Data Warehouse, but the major two were monitoring of clinical operation and improvement of clinical workflow.,Oracle Data Warehouse is a well-known and already validated product. Its performance, technical support, documentation, online community, and sustainability is the best among the area.
It is easy to find and hire good data developers, data architects, and analysts who specialize in Oracle Data Warehouse.
It is easy to develop a financial plan based on the product, as its licensing is systematic. Also, the product's scalability is well developed with licensing policy and it makes it easier to flexibly plan budgets as we need more functionalities and services.,It is very expensive product. But not to mention, there's good reasons why it is expensive.
The product should support more cloud based services. When we made the decision to buy the product (which was 20 years ago,) there was no such thing to consider, but moving to a cloud based data warehouse may promise more scalability, agility, and cost reduction. The new version of Data Warehouse came out on the way, but it looks a bit behind compared to other competitors.
Our healthcare data consists of 30% coded data (such as ICD 10 / SNOMED C,T) but the rests is narrative (such as clinical notes.). Oracle is the best for warehousing standardized data, but not a good choice when considering unstructured data, or a mix of the two.,8,We built an enterprise analytics framework based on the Oracle Data Warehouse, which is a system-wide focus and coordination of people, processes, and technologies that ensures important data assets are leveraged. This led to better decision making, resulting in increased business and clinical value (better outcomes, lower costs, healthier people.)
Through the framework, several benefits were presented quantitively or qualitatively: reduced variation in analytics practice, identification and elimination of duplicated efforts, and removal of unnecessary siloes in information within the enterprise.
The Data Warehouse is well harmonized with advanced analytics tools in our organization such as visualization (Tableau, Cognos,) statistical tools (R, SAS, SPSS), and machine learning (Ayasdi).,Not a member of any user groups,Microsoft SQL Server,Microsoft SQL Server, MySQL, BizFlow BPM SuiteJaehoon LeeMy Oracle DW Review2018-08-02T18:04:22.691ZThe Oracle Data Warehouse is a robust platform being used by many departments for Data Storage, Reporting from Stored Data, & also to build Marketing products. Mostly used for Analytics, as it is easy to query the data & stores a huge amount of data in a pre-processed form required for analytics of a variety of business aspects.,Scalable for the storage of very large data.
Simple queries to pull down the data compared to transactional databases.
Compatibility with variety of other tools, & industry support.,Not effective if we compare it with current Big Data applications.
Other warehouses are better for parallel processing.
Prices are high for few functionalities which are supposed to be bought separately.,7,Very cost effective for large databases.
Very fast results on simple queries.
Analytical functionalities are of wide range, which makes it very cost effective.
For smaller businesses, it might be a great asset.
Some features are supposed to be bought separately, so one needs to consider this before licensing with Oracle DW.,Not a member of any user groups,Hadoop and Tableau Online,Hadoop, Tableau Online, Cloudera EnterpriseKartik ChavanGreat performance for large databases2017-12-12T17:16:32.477ZThe Oracle Data Warehouse provides a robust data warehousing platform that is used across my entire organization. Oracle Data Warehouse is directly used by a wide range of departments from analytics and data sourcing, to finance and marketing. For an organization that deals with huge volumes of data, Oracle DW is a great option for warehousing.,Running analytics queries is made simple on Oracle DWH.
Great support for large databases.
Even while dealing with large volumes of data, the compression capabilities of Oracle DWH ensure that most use cases are scalable.,While the Oracle Data Warehouse provides top notch performance, the pricing options make it unaffordable for most small and medium businesses.
Most add-on features that businesses can’t do without are priced separately.
Customizability options are limited. Cannot modify most features to suit the custom needs of Business.,9,Faster execution of queries, making analytics available quicker.
Easy integration with other tools on top of Oracle DWH saves time and effort for tech teams.
Increases licensing costs for a business significantly.,Not a member of any user groups,Oracle BI Foundation Suite, Oracle Exadata Database Machine and IBM Cognos,IBM Cognos, Oracle BI Foundation Suite, LookerVerified UserComplete Data Warehouse Solution - ODW2017-11-01T18:54:46.909ZOracle Data Warehouse were used for one of our clients to act as an analytics database that stores transactional data like Financial Transaction relation information, Customer Centric Information, Sales and Purchase related Information, Projects and Service related information. The information stored in the Oracle Data Warehouse would help the key business users to pull reports through data cubes which would help them in analyzing different aspects of business. So based on the data points received and the key indicators set, it would enable the business to make informed decisions to grow their business. One example would be to identify customers sales which could be seasonal in nature, so by understanding the patterns of their previous placed order the business can vouch for the customer next time when similar conducive scenario is in place.,Oracle Data Warehouse is scalable and reliable.
Seamless integration with oracle database's using synchronous and asynchronous connectivity thus giving real time data representation to the key business users.
Good performance and high availability of data from the Data Warehouse for analytical reporting.,Like any data warehouse, one needs to conduct a cost benefit analysis to see whether the IT efforts required for implementation of the data warehouse and the cost involved in maintaining the data would be adding monetary values to the organization.
Data Ownership could be one concern where the management needs to decide who would be having what access to the Data Warehouse. So proper configuration of the access would be required, so that there is no breach in data ownership.,7,It helped our clients to have reliable and quick data points and key indicators at their finger tips, which helped them in informed decision making.
The Extract, Transform and Load i.e. the ETL concept is quite seamless to implement.,SQL Data Warehouse and Teradata Data Warehouse ApplianceVerified UserBuild Your Data Warehouse Using Oracle2016-07-20T19:06:06.791ZMy organization designs, builds and maintains a data warehouse for various clients both from public and private sectors. Based on the individual client needs the data warehouse is being used both at the department level and as well as at the entire organization level. The data warehouse is being used to answer and provide insights to the organizations' various activities. Using the data warehouse the organizations are able to derive advanced analytic analysis and in turn increase fraud detection, efficiency and much more.,Able to handle very large data sizes efficiently from a performance, high availability and manageability perspective. This is accomplished through the Oracle Partitioning functionality. Partitioning allows large segments (tables, IOT index-organized tables, indexes) to be broken into smaller segments at the physical layer but treated as a whole at the logical layer.
Provides support for dual-format architecture through Oracle In-Memory functionality. Without any change to application code one can obtain in-memory performance. This functionality enables us to have the tables represented in both the row format and the column format using in-memory format. This is a huge boost for BI/analytic queries since the Oracle optimizer is able to intelligently choose the appropriate format.
Provision to materialize a subset of table data or table joins. This is through materialized views and the optimizer will rewrite the query against the base tables to make use of this materialized view. This provides a huge performance boost and is critical in VLDBs as in a data warehouse. The query rewrite is fully transparent to users.
Provides multiple compression capabilities. This is very useful not only for deducing the storage foot print but as well as increase performance at different layers of the infrastructure including query performance. The compression functionality can be applied against both structured and unstructured data.
With the advent of Engineered Systems (Exadata, Database Machine, SuperCluster) there are specific features and functionalities that can further boost the Oracle data warehouse. These are related to consolidation, Smart Scan, Storage Indexes, EHCC (Exadata hybrid columnar compression) and much more.
RAC - Real Application Clusters (with 2 or more nodes) provides functionality for high availability, performance and scaling as the work load increases. The parallelism is provided both within a node and as well as across nodes. If for any reason a node goes down the data warehouse is still available through other nodes and the running queries are transparently failed over to the surviving nodes.,For the query rewrite related to the materialized views the optimizer at times goes against the base tables. There is room for improvement for the optimizer to make more intelligent choices. There does exist functionality to identify the reason why the optimizer failed to do the rewrite of the original query. This can be further expanded.
On the storage indexes currently there is limitation of only 8 columns. In addition Oracle decides which of the columns are chosen as part of the storage index. It would be nice to see if both of these are addressed in future versions/releases.
Some of the features are 'Options' which would increase the overall licensing cost and is an important factor for certain class of users/clients. It would be nice to see if at least some of the options are standard functionality.,9,Overall the business objective of all of our clients have been met positively with Oracle Data Warehouse. All of the required analysis the users were able to successfully carry out using the warehouse data.
Using a 3-tier architecture with the Oracle Data Warehouse at the back end the mid-tier has been integrated well. This is big plus in providing the necessary tools for end users of the data warehouse to carry out their analysis.
All of the various BI products (OBIEE, Cognos, etc.) are able to use and exploit the various analytic built-in functionalities of the Oracle Data Warehouse.Suresh Muddaveerappa
Unspecified
Oracle Data Warehouse
208 Ratings
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