Organizations do not face identical challenges when using data to gain insights to better run their operations. In previous blogs, we have identified possible challenges that organizations face and professionals that can be hired to help overcome these hurdles. We also discussed the roles that those professionals can play in the organization. 

When looking to hire a data science team, it is important that all hiring decisions be based on the need to solve practical problems. In this post, we will shift attention to discussing factors that need to be considered when looking to hire a data science team. 

In this article, we will discuss what to consider when hiring a data engineer, a data analyst, a business intelligence developer, and a data scientist. Keep in mind that for a successful data-driven organization emphasis must be placed on developing capable teams rather than individuals. A variety of background and experiences bring improved efficiency to the team. Interaction and learning from each other should be promoted within the team to interpret data well and develop the best recommendations. dc Analyst can help you build a team that fits your goals and can help you achieve your vision. 

In our digital economy every organization generates a sizable amount of data. There is real value in understanding and acting on insights and solutions that lay within this data. To be successful at gathering insights from data an organization needs a team of experts with various skill sets to complement each other and work collectively towards a common objective of getting value from the organization's data.

All organizations are not equal. The volume and variety of data differs, therefore, each organization has its unique challenges. The types of challenges faced dictate the type of experts that you need to consider bringing on board. 

Modern business operations generate a variety of data from processes such as sales, customer relationships, human resource management, and product ordering. These multiple data sources are brought into a single repository. Often data analyst create reports for decision makers to aid in decision making and organizational planning. 

Business intelligence (BI) tools are used to identify insights from data repositories. These BI tools connect to different data sources and enable data analysts to equip decision makers with relevant insights from the data. BI tools offer features that are useful for reporting, querying data, online analytical processing (OLAP), and data mining. In this article we will discuss each  BI activity and how they are supported in Tableau, QlikView, and Excel. Lastly, we will look at how PowerPoint can be used to prepare presentations to effectively communicate findings.