Big Data Challenges & Solution

• Managing massive amounts of data - it's in the name - big data is big. Most companies are increasing the amount of data they collect daily. Eventually, the storage capacity a traditional data center can provide will be inadequate which worries many business leaders. To handle this challenge companies are migrating their IT infrastructure to the cloud.
• Integrating data from multiple sources - a business could have analytics data from multiple websites, sharing data from social media, user information from CRM software, email data and more. To deal with this, businesses use data integration software, ETL software, and business intelligence software to map disparate data sources into a common structure and combine them so they can generate accurate reports. 
• Ensuring data quality - if the data is corrupted or incomplete, the results may not be what you expect. But as the sources, types, and quantity of data increase, it can be hard to determine if the data has the quality you need for accurate insights. To handle this challenge companies can use data governance applications and data quality software.
• Keeping data secure - if a business sensitive data, it will become a target of hackers. To protect data from attack, businesses often hire cyber security professionals who keep up to date on security best practices and techniques to secure their systems. Implement data encryption, add access control, endpoint protection software and real time monitoring or the solution for this. 
• Selecting the right big data tools - big data software comes in many varieties, and their capabilities often overlap. Often, the best option is to hire a consultant who can determine which tools will fit best with what your business wants to do with big data. 
• Scaling system and cause efficiently - big data is big, but it doesn't mean you have to process all of your data. The team involved in implementing the solution needs to plan the type of data they need and the schemas they will use before they start building the system so the project doesn't go in the  wrong direction.
• Lack of skilled data professionals - working with untrained personnel can result in dead ends, disruptions of workflow, and errors in processing. Three solutions or higher big data specialists, offer training to your current team members, or choose one of the self service analytics or business intelligence solutions.
• Organizational resistance - another way people can be a challenge to a data project is when they resist change. The bigger an organization is, the more resistant it is to change. Opt to start with a small project and a small team or placing big data experts in leadership rules so they can guide your business towards transformations.