How Business Intelligence will influence your business in 2019

Business Intelligence

Our Business must boost operational efficiencies enterprise-wide if they want to keep up with rapid market and technology shifts.

The recent quote “High Speed Need for Machine Data Analytics,” indicates that organizations are deploying the latest in machine data analytics to benefit big data and internet of things (IoT) efforts, as well as overall IT operations and cyber-security.

Subsequently, they’re increasing revenue and productivity, with quicker incident resolutions and time to market for products and services.

To continue making progress, IT will need to overcome obstacles in infrastructure and staffing demands, as well as difficulties in scaling, managing data ahead of business and technology changes.

“It’s been shown time and again that in all areas, the value of data erodes dramatically as it ages,” proposes the report quite emphatically.  This in other words means the faster you can run analytics on data and subsequently respond to the findings, the greater the chance of achieving measurable value addition to your business. This includes choosing of specific offers, a reduction in customer churnor basket abandonment or resolving a situation in which a company may be left with customer ill-will and poor reviews.

In fact, big data is of far less importance than the notion of ‘fast data.’ How quickly can data be ingested, processed, analyzed, visualized and acted upon?

 Case in point: An estimated 200 IT decision-makers took part in a comprehensive research on this.

Here are the key findings that were uncovered.

Why Business Needs Machine Data Analytics:

Companies are deploying the latest in machine data analytics to benefit big data and internet of things efforts, as well as IT operations and cyber-security.

Protected Production:

81 percent of the IT decision- makers surveyed said their organization uses machine data analytics for technology operations management, and 60 percent cited using it for security.

Data Driven:

51 percent said their company depends on machine data analytics for big data projects, and the same percentage cited internet of things (IoT)

Benefits of Machine Data Analytics:

Faster time to value 24 %
Increased revenue 23 %
Improved productivity 18 %
faster time to resolve I  17 %
faster time to market 11 %.

IoT-Related Machine Data Analytics Areas:

logistics: 52 percent
industrial IoT: 49 percent
predictive maintenance: 39 percent
smart buildings: 36 percent
smart meters: 32 percent.

Routine Function:

86 percent of the IT decision-makers surveyed said that at least 11 people interact with their machine analytics technology at least once a week, and 15 percent said more than 50 people do.

Employees Most Likely to Interact With Machine Analytics:

IT operations and DevOps staff: 78 percent, data analysts: 68 percent, data scientists: 49 percent, business analysts: 38 percent, business users: 36 percent

Preferred Paths:

39 percent of the IT decision-makers surveyed said their machine data analytics technology is open source, 36 percent said it is proprietary, and 25 percent said it is a mixture of both.

Cost Considerations:

Of those using at least some form of open-source tech for machine data analytics 52 percent said they do so due to the low upfront costs, and 49 percent cited low ongoing costs as a factor.

Open Minded:

Of those using some form of open-source tech for machine data analytics, 42 percent said they do so because the IT staff prefers open source, and 23 percent said “it was the best tool for the job.

Challenges of Machine Data Analytics Tech:

Demands on infrastructure resources: 36 percent, demands on staff: 33 percent, difficulties in scaling: 33 percent, slow production of analytics and reports take too long to design: 32 percent, excessive costs: 31 percent

Thus the impact of machine data analytics is very conspicuous. Given its foray into manufacturing and logistics, areas that seem to be having immense potential for data and its interpretation is especially striking.

Given its huge potential job creation, up skilling and industry growth will all have data analytics playing a very important role in the coming decade. How far would it influence decision making? Only time will tell.

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