The embedded analytics market is growing at a rapid rate and will be worth $51.78 billion by 2022. Over the next few years, most organizations will begin to transform their traditional analytical techniques for analyzing business data to more advanced techniques using embedded analytics. If they don’t, they may risk getting left behind their competition. As soon […] 
The embedded analytics market is growing at a rapid rate and will be worth $51.78 billion by 2022. Over the next few years, most organizations will begin to transform their traditional analytical techniques for analyzing business data to more advanced techniques using embedded analytics. If they don’t, they may risk getting left behind their competition.
As soon as this year, with the aid of innovations in embedded analytics and business intelligence (BI), data analytics will begin to be much more accessible to professionals with various backgrounds and specialties across an organization. Analytics and business intelligence will no longer be accessible to analysts alone, and professionals across organizations will be empowered to make data-driven decisions with embedded analytics tools that are easier to use than current tools. In fact, Gartner predicts that 80% of organizations will work to increase data literacy across their workforces over the next few years as innovations in embedded analytics and embedded BI continue to surface with innovations that make for a more user-friendly experience.
Below are the innovations and trends for embedded analytics you’ll want to watch for in 2018, organized by structure and capabilities, and also by features.
Structure and Capabilities
In 2018, embedded analytics will own a more decentralized structure with robust integration capabilities, more options in the cloud, and adaptive security. It will also be easier for users of various backgrounds across an organization to use.
Various Hybrid Cloud Options
As the amount of data that organizations use continues to grow at alarming rates, businesses will consider moving some archivable data out of the cloud and into on-premises databases for backup and security purposes. Platform capabilities for accessing, integrating, transforming, and loading data into a self-contained performance engine with the ability to index, manage, and refresh data loads (self-contained ETL and data storage) will be extremely important. In addition, many organizations will opt for multi-cloud strategies where they have data in multiple cloud locations to help with data security, costs, and performance. Overall, in 2018, there will be a variety of either multi-cloud or on-premises hybrid options (or a mixture of both).
Decentralized Analytics’ Evolution to Governed Data Discovery
As embedded analytics begin to be easier to understand for users across an organization, analytics will become decentralized and data discovery will increase but need to be better governed in 2018. Self-service analytics platforms allow for decentralized workflows and for users to prepare their own data analysis with much less reliance on the IT department. As decentralized analytics becomes more prevalent across an organization, the risk of multiple sources of the truth (of the data) and the integrity of data insight will become a serious concern. So, successful organizations will have to evolve their decentralized analytics to an approach that embraces governed data discovery over time. Governed data discovery will permit individuals across an organization to analyze data for their own use cases, but will require that data analyses and insights still fit within the governed parameters of the organization’s business procedures, policies and objectives.
Read the source article at Innovation Enterprise.