New User Reviews for 2017: Data Warehouse Solutions Roundup

In IT Central Station’s user community, 3009 users follow the Data Warehouse category. Users in our community have already contributed new reviews for Data Warehouse Solutions in 2017 for Oracle Exadata, HPE Vertica, and Oracle Database Appliance. Users discuss the valuable features of the solutions that they use, as well as where they see room for improvement.

“What are the Solution’s Valuable Features?”

Oracle Exadata

Akhilesh Kumar writes about Oracle Exadata’s performance,  “It’s about consolidation of my infrastructure, scalability, high performance, and availability.”

Rakesh Inukonda, adds “Also, we have enabled RAC clusters. That’s one of the main things, as well as high availability. The performance and high availability are really awesome.”

A Senior Principal Consultant at a Tech Consulting Firm sees direct cost benefits from Oracle Exadata’s performance, noting “We see cost saving due to the reduced footprint in the data center and improved performance”

HPE Vertica

Jochen Schlosser highlights a number of good points to the HPE Vertica, noting among them that “The most valuable feature in the solution is ad hoc data analysis. It improved the SLAs for our end clients.”

Oracle Database Appliance

Nitin Vengurlekar writes “The biggest value that customers are seeing, is that it’s easy to install, quick to deploy, and easy to consolidate platforms; as opposed to building an environment from scratch.”

“Where Do You See Room for Improvement?”

Oracle Exadata

Rakesh Inukonda still sees room for improvement to Oracle Exadata’s service, commenting “In the current version we’re using, we had lots of storage issues, disk failures, etc.”  

A Database Architect at a Tech Services Company further notes “One of the major issues was the Write Back Flash Cache. By default, the storage nodes come with write-through. That’s not very good for your OLE DB because it’s not going to hit your flash. It’s going to directly hit your hard disk.”

A Director Of Information Technology comments “They can make it faster and more scalable. Currently, it is not.”

HPE Vertica

Schlosser has little criticism, noting only “[Technical support] could be quicker sometimes, but that’s always the case with big processes.”

Oracle Database Appliance

However, Vengurlekar also points out that “Oracle has done a good job of letting it expand storage, but the number of nodes is still limited to two. This continues to be an issue for customers.”

Curious to learn more about other Data Warehouse Solutions?


Read more new user reviews for Data Warehouse Solutions on IT Central Station.

Data Warehousing Review Roundup: Exadata vs. HP Vertica vs. SQL Server Data Warehouse

This week’s review roundup includes reviews of Data Warehousing solutions. Choosing the right solution can be key for businesses as these solutions integrate data from disparate sources to create a central repository, or Warehouse. Here are some recent reviews from our community members of three Data Warehousing solutions:warehouse

Exadata – “We have a number of statistics collected before cutover on our legacy environment compared to Exadata. Without doing anything other than copying the data across, we saw significant performance gains for most key processes. We receive feedback from users stating how fast the performance is compared to other systems. Performance issues are few and far between. Our database environment is extremely stable compared to the legacy DB configuration. The patching process is a continually evolving. It’s changed drastically over the years and foresee some continued refinement on the horizon, especially when comparing the process to something like ODA. We have one one-off patch which requires a SR with Oracle Support every time the quarterly patch comes out. This is a bit of a pain but I do know sometimes these one-offs get rolled into the quarterly patch or in our case the next version ( ” Read more here.

HP Vertica – “Not having to worry about speed or data volume changes you. Suddenly we began logging and reporting on everything. Where did users click? How long between clicks? How long does it take to type in a credit card number when you’re ready to pay? How much free memory does an iPad 1 have, and how does that change every second? Like all software engineers, we solve problems under constraints, and we had conditioned ourselves to think of logged data volume as a constraint. Suddenly that was no longer a constraint, but I would say it took us a full year to fully appreciate how powerful that was.” Read full review here.

SQL Server Data Warehouse – “Microsoft SQL Server Parallel Data Warehouse provides significant performance boost from 10-100 X times faster for data loading operation. It minimized the cost of design with lower infrastructure requirements. It is designed to provide optimized performance on latest industry hardware. It requires significant infrastructure expertise to implement. Possibility of over specified storage or under specified CPU (need proper planning before starting implementation) It requires significant SQL Server expertise. Microsoft SQL Server Parallel Data Warehouse is purposely built to provide high performance data warehousing. By adopting industry standard hardware it avoids vendor lock-in issue. It is best suited for mid-level to large scale organization.” Read full review here.

Visit IT Central Station to browse real user reviews of Data Warehouse solutions including InfobrightGreenplum, and more!


5 Factors for a Successful Data Warehouse and BI Project

This week’s guest post is by Patrick de Witt who is a senior Business Intelligence and Data Warehouse consultant. Patrick de Witt has experience working with Jaspersoft, Tableau, SAP, Oracle and other BI/DW solutions. Contact us if you would like to be one of our guest bloggers.

I’d like to discuss the factors for a successful data warehouse project and how business intelligence plays a role in it. I know there PDwittare many more factors than I will discuss here, but these are the ones from a business prospective.

The first and most important factor is the business itself. There is no need for a data warehouse when the business can make the right decisions to steer the company with what they already have.

The second factor is the commitment of the business to the project. It is easy to say “We need a data warehouse and we want it by the end of the year, so that we can achieve more business.” But what it means, is that you have to understand and support, that getting there, you will have to assign people from the business to the project, that it will take time and money without getting a return on investment directly.

The third factor is the alignment of the business. As your company starts to grow, go international or acquire companies, you will have to decide how the different organizations within your company have to deliver their data. You will have to set the definitions of the fields and measures you are going to use in the data warehouse.

The fourth factor is to know your organization. Who is going to analyze the data in the data warehouse and what are their capabilities. Can you get support from your IT department or supplier? How much time are you willing and going to spend on analyzing? Depending on the answers to these and other questions you will have to decide which tool will be the best for your needs and purposes.

The fifth factor is about doing it together. That means the project is going to be successful when business meets IT and vice versa. Make a goal for the future, set a deadline as you do need something to give an end to the project. Start a proof-of-concept or a pilot, define the business requirements, set the scope, set the period needed to a couple of months at the highest, decide which tools you will be using and evaluate at the end what has gone well, what can be done better and what you can leave out. If the evaluation says it is better to start over again then don’t be afraid to do so. Break up your project in small pieces and decide together, business and IT, what is going to be delivered and what the most important parts of a small piece will be. The business can then see what has been build in a short time and they are connected to the project and the acceptance level and therefore the success of the project will be greater.

As you can tell, the previous paragraph is quite big- but with a reason. The fifth factor is where the other four factors come together. Without these four factors there is no fifth factor and the success of doing a project is very small, or your IT department or supplier knows everything about your business, needs and strategy. I would find that rather strange.

Now we know all about the business, but what about the IT department? How are you going to sell and manage the data warehouse? Selling means that your customer, the business, has to been shown something periodically. If selling means more (re)work then don’t be afraid of it but regard it as a part of your planning. You will have to slice up the work you are going to do for a project. You can’t really show a data warehouse, so how are you going to sell? This is where business intelligence comes in, not directly as a analyze tool, but as a selling tool. As the business is able to work with the data, they can check the data and will be pleased.

Of course the method mentioned in the previous paragraph is the scrum method of the agile approach, but I won’t talk about this here any further. Using this method is quite unusual for people who are designing and developing data warehouses, as I am one of them. But I am sure this method will lead to better designed above all better used data warehouses and more successful data warehouse projects.

As this is a more general article explaining my own vision, I will discuss in the coming articles more practical cases on how to use data warehouses and business intelligence tools.

Read reviews of Business Intelligence Tools and Data Warehouse solutions from real users at IT Central Station. See reviews of Oracle, Microsoft and other vendors.

How to Successfully Manage BI Dashboard Projects

This week’s guest post is by Fernando Bustillo. He is a Business Intelligence and Data Warehouse expert and has experience working with SAP Business Objects, Oracle, Teradata and other enterprise solutions.  Contact us if you would like to be one of our guest bloggers.


The fact that many dashboards seem to be a single visual screen or eye candy screen could make one believe that it is easy to manage. This could be the first reason why your project will be unsuccessful: underestimating “the enemy”.  In my broad experience working with BI (Business Intelligence) projects, most of them related with dashboards, I have appreciated the difficulty of building a dashboard that needs to be accurate, useful, functional, with quick answers and eye candy. Dashboards are used as a tool for the managers and executives of the organization, and need to be adapted to their requirements and likes. In this review, I’m sharing the major points to consider at the time to manage a successful dashboard project.

What is a dashboard?

There are several definitions of a dashboard. Stephen Few gave us a good example in the March 2004, article titled “Dashboard Confusion” which appeared in Intelligent Enterprise magazine:

A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.

Typical examples are the simple dashboard of a car and the more complicated of an aircraft. In the case of an organization or a company, we as BI designers have to be open minded because the requirements of a dashboard project normally include:

  • Multiple dashboards, each with its own objective
  • Drill-down ability to analyze information
  • Links to detailed reports
  • Additional functionality: navigation, what-if analysis, ability to share information, internal communication, export data, print, send by e-mail, etc.
  • Metadata information

Car dashboard:

guestBI1Sales dashboard:


Dashboard success factors you have to know

Depending on the dashboard type, you have to pay special attention to different factors. Strategic dashboards are normally used for monitoring the global company’s progress in achieving predefined goals. In this type of dashboard, users are at the top of the hierarchy, so the quality of data is very important. In addition to consolidating the information, it is important to ensure the information is correct and accurate. Nobody wants the CEO consulting the dashboard with incomplete or erroneous information. The information must be complete and valid before it is visualized on the dashboard.

Tactical dashboards are usually used for tracing the trends in relation to company’s goals and initiatives. This type of dashboard normally incorporates three types of data: detailed, summarized and historical. The users normally navigate from the first visual screen to the OLAP (On Line Analytical Process) system to analyze the information and to review detailed reports. This explains the need for a deep functional system with a quick response time, which is a challenge if the amount of data is large.

Operational dashboards are used for monitoring and analyzing the most detailed company’s activities in a given department. Normally this is related with real time or near real time, so decisions about ETL (Extract Transformation Load) process are important. Most of the operational software include their own dashboard modules. The use of this module bypasses the problem of load time, but normally with a loss of functionality. The difference of project development time is very large.

If there isn’t an indicators dictionary, you have to create it. Establishing a precise and accurate definition of metrics and indicators will facilitate the understanding of the dashboard and further promotion. End users have to understand the meaning of the dashboard if they are going to utilize it. Also, the indicators definition has to be accessible from the dashboard.

One needs to ask, is all data available? Very often, strategic data are not saved in any corporate database; instead they are saved in personal documents like spreadsheets and presentations. This presents a difficultly in the process to load the data in the dashboard.

The dashboard needs to be integrated into the organization, so it is important to consider corporative aspects: logos, colors, fonts, menu, etc. Are there similar systems? If so, use a similar look and feel.

What’s better, a very precise classic table with the exact data or the newest graphs full of colors and shapes?


The world of data visualization is changing rapidly, with the trend to use complex graphs and infographic techniques to visualize information in an impactful way. Also the concept of big data is changing our relationship with the world of information. That’s perfect for powerful presentation, but not always for a dashboard. We have to decide in each dashboard the graphic elements that better represent the business event we need to monitor. Speedometers, gauges and meters are a current trend, but they use so much space to represent only an indicator. Pie charts are good for comparison, but they are not precise. Tables are boring, but accurate. Bar and line charts are classic, but functional. A combination of areas, bars and lines on a chart is often a good choice.

The dashboard is not a static screen, since the user must interact with it. Not only print and export, but also select and filter data. Using charts as a filter should be very intuitive. Users expect tables to have drill-down functionality. The navigation has to be clear and intuitive. At any time, users need to know the level of information that they are consulting.

Manage expectations. Because dashboard tools offer more and more built-in functionality, it is common to see users waiting for the latest function they have heard or waiting for drill-down ability that you have not developed. It is important to show examples of other dashboards developed with the same tool. Building prototypes is one of the best ways to manage expectations. It has to be clear how users will interact with the dashboard.

Don’t wait until the end of the project to show the dashboard. Designing a good dashboard is not easy, no matter the experience you have. It is not possible to get it right the first time, so you have to build prototypes and quick developments to validate it with end users. They have to validate navigations, graphs, colors, fonts, data and all the important functions.

Dashboard development can have the potential to never end! This could be a great business opportunity for consulting companies but a headache for the project manager. As long as end users like the dashboard, they often want to make changes to incorporate more information and functionality. At this moment, it is important to have a limited scoped project.

As the world changes, business changes. Dashboards have to change according to business needs. Don’t forget to manage a maintenance agreement to guarantee that the dashboard will evolve according to new requirements.


A dashboard project could be an easy project to manage with few resources in a short time, or a big project that involves multiple resources with different skills: data visualization, business knowledge, database experts, technicians, consultants and managers. We need a good project definition and limited scope for making a realistic plan. To avoid failure with user’s expectations, make prototypes and rapid developments to show preliminary dashboards to the end user. If the project is large, separate it into phases for short-term results.

Read reviews of Business Intelligence Tools from real users at IT Central Station. See reviews of Microsoft, Tableau, and other BI vendors.