Data Analytics using the Splunk Platform
Learn Splunk ⇒ Pass the Splunk Certification Exam ⇒ Become Instantly Marketable
Land a Job ⇒ Become a Big Data & Data Analytics Ninja
Splunk Fundamentals Course Description
Splunk is a leading big data platform that provides a unified way to organize and extract real-time insights from massive amounts of machine data from virtually any source.
Splunk software/platform will be leveraged throughout the duration of this course to teach students the fundamentals of big data and data analytics by showing them how to unlock the hidden value of big data. By utilizing the Splunk Platform we will be able to show students how to collect, index, search, analyze and visualize data in one place.
Participants who successfully complete this course will be prepared to complete the Splunk Core Certified User exam.
3 Reasons Why You Should Take This Course
- Jobs, Jobs, Jobs – Job Opportunities and High Demand for Analytics Professionals
Put simply, data analysts are valuable, and with a looming skills shortage on the horizon, as more and more businesses and sectors start working with big data, this value is only going to increase.
- Data analytics is top of mind for organizations of all sizes
Almost every top organization considers data analytics a critical factor of their business growth. As big data analytics professional, you will be analyzing an immense volume of data in order to arrive at critical business insights, which can have a huge impact on a company’s profitability, policies, and marketing strategies.
- High Salaries
Strong demand for data analytics skills is boosting the wages for qualified professionals. As the demand steadily increases and the supply remains low, data analytics professionals are getting paid more and more. This trend is evident across the globe as more and more companies realize just how important these professionals are to the organization.
2020 Course Dates
Log in or create your account with UIS Continuing and Professional Education, and then register using the links below.
- Register June 11 to July 9 (Registration deadline May 20)
- September 10 to October 8
- October 22 to November 19
Each week, participants will join an instructor-led lecture with labs, delivered via a virtual classroom from 4:00 p.m. to 6:00 p.m. on Thursdays. Participants will have access to a learning management system with learning materials and homework.
After successfully completing the final quiz, participants will earn a digital badge from UIS and bitsIO, Inc.
This course, Splunk Fundamentals, Part 1, prepares students to take the Splunk Core Certified User exam from Pearson Vue.
Course participants should have basic computing skills for navigating the LMS and virtual classroom and
- Work experience with a basic understanding of data analytics
- Higher education coursework with a basic understanding of data analytics
This course is being led and facilitated by bitsIO, Inc. bitsIO is a leading Splunk Elite Partner based in Springfield, Illinois. As one of the leading Splunk Partners in the industry bitsIO, Inc. has over two decades of expertise in the IT domain and a track record of deploying Splunk technologies to national and international companies, both large and small.
The registration fee for the 4-week course is $500, a 50% savings over other Splunk instructor-led online learning opportunities.
If students decide to take the Splunk Core Certified User exam, they will register and take the industry certification exam through Pearson Vue. The current cost for the exam is $150.00.
What is Big Data?
History of big data and data analytics
The concept of big data is not new; most organizations understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value and derive competitive advantages from it. But even in the early 20th century, decades before anyone used the term “big data,” businesses were using basic analytics (essentially numbers on a spreadsheet that were manually examined) to uncover insights and trends.
The new benefits that big data and data analytics brings to the table, however, are speed and efficiency. A few years ago businesses would have gathered information, run analytics, and unearthed information that could be used for future decisions – today those same businesses, by leveraging big data analytics can identify insights for “immediate” decisions. The ability to work faster with much larger datasets – and stay agile – gives organizations a competitive edge they didn’t have before.
Why is big data analytics important?
Big data analytics helps organizations harness their data and use it to identify new opportunities and uncover insights & trends. This leads to smarter business decisions, efficient operations, higher profits, and ultimately happier customers. Industry reports show that companies derive value from big data analytics in the following ways:
- Cost reduction. Big data technologies bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.
- Faster, better decision making. With the speed of big data technologies, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.
- New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. This leads to businesses creating new products to meet customers’ needs – which ultimately drives profits and customer satisfaction.
Why should I care?
If you want to succeed in this digital world that is creating a knowledge-based society, you must study trends. Right from start-ups to non-profits to large multinational conglomerate companies, everyone depends on data to formulate improved strategies for the future of their companies.
Now picture yourself as the person these companies depend on before they make any big business decision. That is precisely why you should study data science and big data analytics.