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Avoid the Top 10 Mistakes Made By Beginning Business Intelligence Technologies

Latest business intelligence technologies like AI, Augmented Reality, IoT and many are incorporated in the Retail software management by Zuci Systems. They provide the best platform for Omnichannel retailing. Zuci Systems is the market leader in providing an Inventory management system for several organizations.

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Avoid the Top 10 Mistakes Made By Beginning Business Intelligence Technologies

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  1. Avoid the Top 10 Mistakes Made By Beginning Business Intelligence Technologies BIT adoption shot to fame in the world of business enterprises because of a profound demand for real-time and actionable information to help executives and managers make critical and sound decisions. However, one has to avoid the following 10 grey areas when dealing with BIT: #1 User Engagement Mistakes Not actively engaging targeted end-users is the first mistake to be avoided. Even the best technologies in ​business intelligence ​like data warehousing, Ad Hoc Reporting, Cloud Data Services can fail due to a lack of end-user involvement. #2 Divorce between the business strategy and the BI strategy In most cases, there is a lack of alignment between the business and the BI strategy. BI often becomes the brainchild of either the IT or the users. A middle-of-the-road approach is needed for drawing insightful advantages.

  2. #3 The Build it and leave it culture Many enterprises commit the fatal error of considering BI as a one-time investment. The BI architecture must be revisited periodically. Data quality, staff training and ​data analysis​ are recurring and not one-off processes. #4 Failure to factor-in legal requirements With every amendment to the GDPR (The General Data Protection Regulation), the business intelligence technologies need to be teethed accordingly to meet the compliance requirements. In a recent survey involving 2679 participants, BI-Survey1 identified the quality of data, management of master data, data discovery and visualization as the key trends in BI for 2019. #5Choosing a non-scalable and non-adaptable BI solution The BI solution today may not suffice the challenges of tomorrow. As your organization grows so do the demands for BI tools. The technologies used must be future ready and expandable. #6Allowing the formation of data silos Multiple versions of the same data are called data siloes that challenge the profitable implementation of BIT. Self-service and data centralization will help businesses reinventing the wheel and avoid costly repetitive storage and retrieval of data. #7 Failure to secure buy-in from key stakeholders Many firms do the mistake of getting the nod only from the senior management cadre. The naysayers to BI may also arise from the middle rung, for instance, the sales or the marketing team. #8 Flaws in Data Integration McKinsey2 identifies large disruption potential in orthogonal data and the way it can lead to a revolution in data discovery and radical personalization. Failure to integrate and make data BI ready will cost organizations dearly.

  3. #9 Lack of differentiation between BI and Software Migration BI technology implementation requires data from legacy systems to be migrated into a cutting-edge tech-based ecosystem. This is a phase of BI and mistaking it to be the indicator of successful BI implementation is a common mistake. #10 Underestimation of training and user enablement costs Many BI software kits promise an end-to-end onboarding period of 4-5 days or a week, at the maximum. But user familiarization and employee training is a longer investment and overlooking the same can become detrimental.

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