Business Insights and Data visualization are one of the most critical and must-dos for retailers of today to enable themselves to provide more value to their end customers and also to optimize their expenses because as they rightly say DATA HAS ALL THE ANSWERS! And should be used efficiently to provide for all the problems.With customers more willing to share data and with ever-growing avenues to capture information, the retailers can benefit in a spectacular manner from the vast reservoirs of data they sit on.Potential of data is huge but there always have been these challenges which have inhibited retailers to make full use of data available to them. Having worked with e-Commerce companies around the globe of multiple sizes and varying data capabilities, following are some of the top challenges that an e-Commerce company faces when it comes to utilizing data for deep business insights: Data Availability and AccessWhen enterprise and cloud systems supporting a commerce platform go live, the least focus is on conserving data and maintaining it for insights in the future. So, when retailers want to emphasis on data intelligence and look for discernments at a later stage, their platform topology has usually become too complicated with all the external and third-party integrations and they realize they not only not have access to a lot of their data because of insufficient documentation, lack of knowledge, changes in authorizations and employee turnover but also the data is not in the shape and format they can use to derive actionable insights.Data QualityOne of the biggest challenges for a BI team is Data Quality and longer the legacy of the platform greater the quality issues in the data – inaccurate, duplicate, obsolete data are some of the major caveats that a team faces. The way forward with bad data becomes more challenging because to provide accurate insights and visualizations there is no scope for data quality issues. This typically forks the data team to deviate from discovering insights to cleaning and shaping the data. This in itself poses many challenges because there is usually not one person who can guide the team on what is right and what is wrong and provide knowledge on correct logic behind data available to them. This in particular causes the most delays in a BI team trying to deliver reports and dashboards based on the commerce data availableNew IntegrationsRetailers end up capturing tons of data in both structured and unstructured format which may or may not be ideal for data analysis and may not be setup in a way that data analysis can be done on it. Overtime as new platforms keep getting added to the entire e-Commerce ecosystem, the implementations do not necessarily keep in mind data sync, data models and other data quality policies which results in greater disconnect in the data and leads to bigger issues for teams trying to extract and clean data.Data Privacy and fear of breachRetailers have a big fear of data and privacy breach and rightly so. Most of the teams do not understand the protocols and standards of maintaining data or how much flexibility they have to run their customer data through 3rd party tools which causes them to be content with minimalistic insights they can get from the current state and they do not like to venture into data analytics and new practices which might require integrations with tools and technologies which are not up to security standards that are required to maintain privacy for their data.Dispersed data sourcesRetailers usually have separate platforms focusing on marketing, inventory, operations, commerce etc. The problem arises when each system is defined keeping only itself in mind and insights from that one system usually have a very siloed view of a particular domain and hence fail to bring the bigger picture out providing metrics that cover the entire e-commerce functioning for retailers. To truly make use of data, they have to see it together and from one lens only then impactful data stories can come out.Lack of intent, vision and investmentAll of the afore-mentioned issues stem from the fact that the intent to get insights from data and make resources useful is not present when e-Commerce platforms are brought to life. The vision for the teams and executives is to get their platforms and sites off the ground and in doing that they fail to look at long-term picture and instill data related protocols and best practices in the team.Data mining, data cleaning, data science and visualizations all require investments and time especially a lot more if retailers have not prioritized their data practice at the start. These are some of the many challenges that lot of retailers face when they want to use their data to get insights from and they should be wary of falling into these data troughs which cause delays and huge costs to get out from.