What is Insights-as-a-Service (IaaS)?

                         Insights-as-a-Service uses predictive analytics and business intelligence to glean effective actions from data warehouses. Companies often don’t have the robust infrastructure and IT personnel needed to parse valuable insights from the enormous volumes of data that they constantly produce.

IaaS platforms address this need for in-depth analytics on the cloud and provide solutions to unique data-specific challenges. Moreover, it allows companies to reduce their costs significantly by removing the need for data scientists and complex infrastructure required to run analytics on-premise.

IaaS focuses on providing a visually appealing and comprehensive data set that helps optimize operations and enhance revenues. This is vitally important for companies that keep their data in separate silos, as well as attempt to scan it manually, or on-premise.

IaaS manages to merge both internal and third-party data sets, and uses AI to efficiently scan these sets quickly. IaaS’ cloud-based embedded analytics are a cost-effective way for companies to go from simply viewing data and interpreting it historically to actively analyzing and deriving real-time insights from it.

How can I use Insights-as-a-Service?

One common problem many companies—and especially larger ones—face is the fragmentation of data and its impact on decision-making. Different departments use specific sets and limit their insights, leading to less effective outcomes.

Nevertheless, many companies are content to keep data siloed, even when they use tools which can capture various data streams simultaneously. The frequent disconnect between these and other departments means that companies aren’t getting the most out of their data.

Nowhere is this more apparent than CRM. Even if every department in the company uses the same CRM platform, customer profiles are likely to be fragmented across different accounts and listings. IaaS can create a more holistic approach to consumer data by creating a more comprehensive picture.

Instead of fragmenting data, IaaS platforms let companies create a unified data set that is easily scanned and queried for better insights. Combined with AI and machine learning algorithms, IaaS also expedites the process of deriving insights.

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For companies operating on a smaller budget, IaaS’ cloud platform offers a secure, scalable approach to parsing and monetizing burgeoning datastreams. IaaS solutions are constantly evolving to address companies’ specific data problems, helping them discover what data is redundant, what external data them should purchase, and how this data can be meaningful to their bottom line.

Types of big data Insights-as-a-service uses

Insights-as-a-service cannot deliver independently. It depends on a lot of data sources for delivering actionable insights. Mainly, Insights-as-a-service uses the following data types:

• Company data: This is the data stored by the company in the SaaS applications. Company data could encompass a wide range of data such as financial data and results, stocks, employee details, keyword performance, and business process data.  Basically, the company decides the type of data it stores.
• Usage data: Usage data refers to the data captured during the usage of the SaaS applications. Whenever a module is accessed, used, configured or removed, the data is captured in a web-compatible format. For example, if a few fields in an application are frequently accessed, that constitutes an interesting insight.
• Syndicated data: This is the data collected from third party sources such as LinkedIn, Bloomberg, other open source applications and Facebook. When syndicated data is combined with the two types of data described above, it can result in some deep, relevant insights.
• What should not be missed is the correlation between the SaaS growth and that of the Insights as Service solutions. Both are directly proportional. So, given the fact that SaaS is on the rise, expect an upsurge in the Insights as Service sector. The image below shows the growth statistics of SaaS.

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How does the service work?

• There is a certain process to be followed for the solution to work:
• The service collects data from various sources.
• The services may employ the domain experts through the entire process if need be.
• Apart from the industry standard domain processes that are involved, the service providers also use much of the best practices in the industry.

Data, insights and analytics and best practices combine to generate actionable insights for specific industries. These plans are specific and concrete which are intended to help companies achieve their business goals.

The Action Generator, which is a key component of the Insights-as-a-service solutions, is used to generate a set of steps or actions that a business needs to take to reach its business goals. For example, the Action Generator of D’Bara, which gives solutions for customer acquisition and retention, generates its actions from the deviation-detection analysis.

How has this trend been growing?

For organizations around the world, investing in the process of extracting actionable insights from data can be a proposition that proves to be extremely costly. To do this, at a reasonable cost, organizations need to have their resources and infrastructure. This stands as one of the main reasons why Insights as a service has been a timely solution. Given below is data given by KDNuggets, that shows how rapidly insights as a service has grown in the last couple of years.

Companies are said to be directing close to 15% of their IT investments towards Insights-as-a-service and other cloud-based offerings. The investment is going to increase to 35% by 2021.

By 2016, it is said that 50% of the data of all organizations will be stored in the cloud.

The market value of big data and Insights-as-a-service is expected to reach revenue of 17 million dollars in 2015 and 88 billion dollars by 2021.

The big data-based services market, of which the Insights-as-a-service is a part, is expected to reach 30 billion dollars by 2021. Currently, it stands at 2.55 billion dollars.

The industries that will be using the Insights-as-a-service and other SaaS solutions the most are business, finance, retail, media, and telecommunications.