Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Business Intelligence Maturity Assessment: Data Visualization and Data Strategy Services
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Visualization > Business Intelligence Maturity Assessment: Data Visualization and Data Strategy Services
AnalyticsBusiness IntelligenceData ManagementData VisualizationData WarehousingModelingSQL

Business Intelligence Maturity Assessment: Data Visualization and Data Strategy Services

IndexAnalytics
IndexAnalytics
8 Min Read
business intelligence Technology
SHARE

business intelligence Technology

business intelligence Technology

How do you assess the overall health and maturity of your Business Intelligence initiative? Big Data Analytics has recently received significant attention in the press and media. But this article is the first in a series that reviews the topics to be considered when reviewing the current status of a traditional Business Intelligence initiative. In part one, the functional areas of Data Visualization Services and Data Strategy Services are covered. In subsequent entries, Data Integration Services and BI tools and technologies will be discussed. 

Data Visualization Services:

More Read

First Look – Incanto
Building a Private Cloud: A Strategic Guide
Smart Ways of Using Google API for Optimum Results
#18: Here’s a thought…
How are Supply Chain Executives dealing with today’s…

1. Enterprise-focused BI solution – Usually, BI initiatives tend to be focused on a particular functional area within an organization, and that area typically is the one that “owns” the initiative in terms of providing requirements and setting priorities. However, this introduces the problem of “data silos” and “data fiefdoms.” For example, the Sales team has their own analytics solution, but the procurement and purchasing division wants to build their own reporting solution that focuses on their specific requirements.  This kind of behavior needs to be discouraged at the executive leadership level unless there is a compelling reason to go down that path. An “Enterprise-focused” BI solution should address all the data needs of the organization spanning multiple functional areas. For example, what if the senior leadership of a company wanted to know how many orders a top customer placed during a span of three months while his call center team needs to know the reason it has received an unacceptable amount of call about the quality of the product? This example involves merging sales analytics with contact center analytics and building an integrated enterprise Data Warehouse.

2. Transactional/Operational reporting vs. BI Analytics – One of the common problems encountered by Business Intelligence initiatives is that they are often needed for day-to-day transactional or operational business requirements. Though that a valid need that can be supported by the BI initiative, we recommend that the BI solution consider building multiple aggregated summary reports that help users identify trends and patterns over a period of time. This approach helps users think about the bigger picture without letting them get mired in the detailed data. In addition, this also helps in addressing the data needs of different levels of users in the organization. Not everyone in the organization might want to see every single order placed at a particular store location, or all the purchases made by the individuals in a division using the corporate card.

3. Executive Dashboards and KPI scorecards capability – This topic is similar to the previous example of accounting for different audiences of a BI solution. Executive management may have interest in tracking such items as the performance of different components of an organization or the particular goals set at the Senior Leadership level. This can be accomplished using Executive Dashboards and KPIs. These Dashboards or KPIs can be integrated into an existing intranet portal so that the entire user community can view the progress made on an overall enterprise goal. This effort typically also provides executive sponsorship for the BI initiative as well as any support for the effort from the Senior Leadership. Both can be very helpful for the overall success of the BI initiative. For more 

Dashboard data tool

discussion about the different Data Visualization capabilities of a BI tool, please refer to the blog post written earlier.

 

4. Overemphasis on technology – IT organizations tend to get carried away when trying to implement the latest BI tool features and functionality. However, the emphasis needs to be placed on how the tool will enable the users in enhancing the business processes. If a particular cutting edge feature of a BI tool isn’t directly relevant to the overall data strategy of the organization, it doesn’t make sense to implement that functionality and cause additional confusion in the user community.big data integration

Data Strategy Services:

1. Enterprise-wide centralized metadata repository – We recommend that a single, enterprise-wide, centralized repository be built that contains the definitions of all the reporting objects like metrics/measures, attributes/variables and filters. Inconsistent object definitions between different groups of the same organization is a problem I’ve encountered with every organization I worked with in the past 10 years. A few years ago, one of the top manufacturing companies I was involved with couldn’t easily define a prominent metric like “Spend Amount.” Is it the amount vouchered? The amount paid? The amount invoiced? Does it include internal inter-division payments? A single metric can be defined multiple ways depending on the sub-set of the business community involved. Often, there is no repository that captures all of these definitions.  Lack of object definition standardization and insufficient business user participation during the requirements gathering can be the root cause of many issues that would cause the team to spend considerable amount of time trouble-shooting and root-causing reporting issues. So, we recommend that all of the object definitions be captured at single location and shared with the entire organization for reference. This “repository” will also be helpful when you are trying to determine the set of objects impacted by a source system change.

2. BI solution utilization – It is really helpful if you can monitor the usage of the BI solution after it has been deployed. Questions such as “how many users are using the solution?”, “how frequently are they using?”, “are they using some reports/objects more than the others?” can help the BI implementation in determining the focus areas for post-deployment support of the BI solution. Monitoring the usage of the BI solution can also drive the ROI calculation of the BI initiative. Executive management could then use this to determine if a subsequent phase of the BI initiative needs to be sponsored, and if there are any lessons learned from the previously deployed BI solution.

3. Training and outreach – The BI team should consider creating extensive reference material and training content that is geared to the business users. Such a library can be used to review the content implemented in the BI solution and explore how the data is stored. Training sessions should be conducted at frequent/regular intervals, and feedback from users should be considered to constantly tune and enhance the training material. Additionally, User Guides that package all of that information together are also helpful in communicating the technical implementation of the business user’s requirements.

Finally, we really want to emphasize that BI solution implemented is not the end-game but it is just a tool or framework implemented to help the user community enhance their business processes.

TAGGED:best practices
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

protecting patient data
How to Protect Psychotherapy Data in a Digital Practice
Big Data Exclusive Security
data analytics
How Data Analytics Can Help You Construct A Financial Weather Map
Analytics Exclusive Infographic
AI use in payment methods
AI Shows How Payment Delays Disrupt Your Business
Artificial Intelligence Exclusive Infographic
financial analytics
Financial Analytics Shows The Hidden Cost Of Not Switching Systems
Analytics Exclusive Infographic

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

business intelligence tools
Best PracticesBusiness IntelligenceExclusive

10 Best Practices For Business Intelligence Dashboards

15 Min Read

Which came first, the Data Quality Tool or the Business Need?

8 Min Read
customer relationship management
Big Data

CRM: Businesses Should Walk Before They Run

3 Min Read

The Battle for the Status Quo

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?