Contact Us
×

Day: April 13, 2021

What is the Difference Between SAFe and Scrum Master Certification

Posted on by Imarticus

What Exactly is Scrum and What is Scrum Master?

Scrum is a structure that helps build team working habits. It encourages teams to use past experiences to learn from them, self organise when working on an issue and analyse both their losses and wins in order to improve. This agile management device defines a set of meetings, instruments and roles which work together in order to help teams in structuring and managing their work.

Scrum masters help in facilitating scrum and is an agile framework that is lightweight. It focuses on time sensitive iterations called sprints and as a facilitator it acts as almost a coach to the team called servant leader. Scrum leaders must consider opportunities that will help the team improve its quality of work while remaining committed to the scrum’s foundation values.

What is Scrum Master Certification and What Does it Entail?

Scrum master certification helps people understand what good scrum is as per official scrum guides. The basis of the certification is the scrum guide. The certified exam for this is lightweight with 100 multiple choice questions drawn over a span of 2 hours and is taken after scrum master training.

What is SAFe?

SAFe happens to be a globally leading framework used to scale Agile across enterprises. It is designed to increase efficiency by driving a faster time to market ratio thus increasing productivity. Lean-Agile transformation is a combination of leadership engagement and education as well as training. Its role-based curriculum assists enterprises in bettering results.

What is SAFe certification and what does it entail?

This certification assists in resolving coordination issues in three stages:

1. Introducing management at an executive level thus passing on available budgets onto different value streams.
2. Organising the value stream within the company in order to generate various products and distinct services.
3. Encouraging more roles and practices at different stream levels.
Its basis is the website and training material provided by them in order to cover a larger span of content than just plain scrum.

The SAFe examination is a lot harder to clear considering its huge course content and highly advanced level of certification. There are 70 questions with a requirement of at least 75% to clear the exam. The exam like the scrum master examination requires training and preparation.

The differences in scrum master certification and SAFe certification are as follows:

Scrum master certification:

  1. It is structured and curated for a single team.
  2. It has three primary operational roles – Scrum Master, it’s development teams and the owner of the product.
  3. Usually four ceremonies are part of this. They are, daily scrum, stand-up meeting, deciding plan and review. This helps in reflecting on issues and rectifying them.
  4. The scrum master course for certification usually fits into one framework.
  5. It is mostly self-organised with cross-functional teams being co-located.
  6. It is more of a foundation level certificate. It can be used as a stepping stone to be able to proceed to more complicated certifications like SAFe.

SAFe certification:

  1. This could entail a team of a hundred to even a thousand members for turnkey projects.
  2. It is used majorly in scaled project environment groups.
  3. The roles covered here, under SAFe, are beyond scrum master certification. Its roles may even go as high as portfolio and program management levels.
  4. It is not just restricted to team level but can cover ceremonies beyond that as well.
  5. Covering a combination of multiple frameworks, it proves to be advanced and versatile.
  6. It can be located in a multitude of sites due to its time flexibility allowing it to be found in different time zones as well. They can thus be called a centralised and decentralised decision making environment.

With Jobs at Risk, can a Career in Big Data Keep You Safe?

Posted on by Imarticus

Data powers the information economy just like oil powers industrial economy. No wonder they say, “data is the new oil”. A critical asset to many industries, data science and AI changed the way information is gathered and processed. Even when COVID-19 hit the global economy, leading to job cuts and hiring freeze, data science remained unaffected.

While companies do not debate on the importance of data science, collecting and storing the huge volume of data was a big challenge. With limited capabilities, companies had a big struggle to maintain and process data. However, AI and cloud-based technologies provide a solution to this problem. These technologies have created better job opportunities for data professionals than ever before. If you are aspiring for a data analyst career, there isn’t a better time than this.

Why Big Data?

The world is consumer-centric and will remain so despite the hard hits on the economy. Consumerism is the driving force that creates revenue, and job opportunities. From healthcare to e-commerce, all industries are data-driven. The data requirement changes from one business to another, from one company to another. But the enormous amount of unstructured data can be collected using various tools and techniques, organized and structured according to the business needs.

No matter the business is consumer data is vital to all businesses. The tech giants like Google, Amazon etc, and the social media giants like Facebook have been using the potential of data to achieve a competitive advantage over their rivals. And the result is pretty much evident. They are far ahead of their competitors.

What is common among all of them is that they collect large swathes of data regarding their customers – right from what products they buy, which products they ditched after adding to the cart, which posts get better engagement, how long does a person spend time on their webpages – every single move of their customer after arriving on their website is tracked, processed and analyzed to make better business decisions.

The global health crisis saw the extensive application of data, how it can be used to manage a crisis better. From contact tracing, health screening and mitigating the spread. Many apps were developed to help contain the spread, leveraging the GPS to identify the COVID-19 hotspots.

The Increasing Demand for Data Scientists

COVID-19 has indeed changed the way the world functions. With more people staying indoors, individuals flocking the internet also increased. From work to shopping, everything is being done online. And this has increased the requirements for data scientists. While many companies struggle to acclimatize and manage their current employees logging in from a remote place, Tech firms are out with a pressing need to recruit more talents.

With more students and professionals active online, the need for online tools and platforms is growing, and this has led to the demand for an intense expansion of their talent pool.

AI and cybersecurity talents are the most coveted as many companies need technical support in digitizing their businesses. This calls for the improvement of data security measures and to enhance automation to reduce the on-site manpower.

Firms that rely on AI-powered software and those which provide such platforms are on a lookout for technical talents including software engineers and data analysts. Furthermore, financial services companies are also gearing up to become market-ready when the economy reopens. They have started headhunting for people with risk management and data analytics skills to cater to the recent spike in digital banking and online payments activities.

Data Science Online CourseData science is one of those areas not affected by COVID-19. In fact, the pandemic and the enforced stay-ins have resulted in an increased demand for data scientists. If you are a new graduate, take this opportunity to make the most out of the current market situation.

Enrolling in a Big Data Analytics Course could help you land on a lucrative career in data analytics and big data.