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A roadmap for improving reporting and data analytics

All custom software and software packages come with reporting functionality. That functionality is almost always sufficient to successfully launch the application. Soon after launch the world changes because successful applications grow in terms of.

As this growth continues, the previously sufficient reporting functionality becomes inadequate and the chorus of end-user complaints becomes louder. Here’s a roadmap that CIOs can apply to respond to mounting frustrations. The roadmap will keep end-users and management happy as the application continues to grow in usage and value to the organization. The steps in the roadmap are listed in increasing order of cost, technical complexity, and business value.

As end-user familiarity with the application and hopefully their sophistication grows, their frustration with the limitations of the available reports will increase. In addition to developing new reports, the existing reporting functionality can be enhanced with features such as:

While this roadmap step often satisfies most end-users, it causes a proliferation of Excel workbooks that are not managed for consistency and lead to multiple versions of the truth.

Is your data warehouse causing heart failure in the executive suite due to development cost overruns and surprisingly high operating.

Initially the online and the reporting functionality of the application both access the same datastore running on a single computing resource. As usage of the application grows, performance will degrade. This problem can be addressed by:

This roadmap step ensures excellent online response times. However, this action:

As end-user sophistication continues to grow, the stream of enhancement requests for new reporting functionality can’t be fulfilled at a reasonable level of IT staff. At this point, the demand for better information access can be addressed by adding ad-hoc query functionality that includes features for:

This roadmap step greatly increases the sophistication of reporting and querying functionality available to all end-users. It takes the pressure off IT resources to produce more and more reports. However, this action:

Organizations migrate to cloud-based services or migrate their custom applications to the cloud in pursuit of the following benefits: Near-instant.

As the consumption of computing resources for reporting and querying grows, the ability to keep upgrading a single computing resource becomes increasingly difficult even in a cloud environment where adding resources is easy. Now it’s time to duplicate the online datastore onto a separate computing resource and point the report and query load to the new database instance.
Typically, the report and query instance is refreshed nightly. In most organizations, basing reports and queries on the data available at the end of the previous business day is sufficient.
Your DBMS supports replication and synchronization to refresh your report and query instance. You will likely start with replication because it’s fast and easy to develop and manage. As requirements become more complex, you may move to synchronization.
This roadmap step delivers:

However, this action comes at a cost for more:

As management asks for more variance analysis and trend forecasting, end-users will push Excel charts beyond its capability and request more sophisticated data analytics functionality. Business intelligence or data analytics can be addressed by adding functionality that includes features such as:

This roadmap step greatly increases the sophistication of querying and charting functionality available to all end-users. However, this action:

At a time when digital transformation is one of the biggest buzzwords in the business market, a new study by.

As the consumption of computing resources for reports and queries continues to grow, the online query performance and elapsed time for report production will inevitably suffer.
The next roadmap step is to upgrade the memory of your computing environment significantly to implement in-memory processing by the DBMS. As we all know, the elapsed time to complete a data fetch in memory is a tiny fraction of the time required to complete the same data fetch from disk. This action will:

However, this action increases resource consumption and therefore operating costs.

As the consumption of computing resources for reporting and querying continues to grow, the inefficiencies associated with a large report and query load accessing a datastore designed for transaction processing causes costs to skyrocket and performance to plummet.
Now it’s time to consider changes to the data model for the datastore of the report and query environment.

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