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Here Are The Top 5 Skills To Learn In 2025

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By Jack Kelly

As we stand on the cusp of a new year, the job market continues to evolve at an unprecedented pace, driven by technological advancements and shifting economic realities. In this dynamic environment, professionals across all industries are recognizing the critical importance of upskilling and reskilling to remain competitive and relevant.

The coming year presents a golden opportunity to invest in yourself by acquiring the in-demand skills that employers are actively seeking, ensuring you’re well-positioned for career growth and new opportunities in an increasingly digital and automated world.

The rapid acceleration of digital transformation, catalysed by recent global events, has reshaped the way businesses operate and the skills they require from their workforce. From artificial intelligence and data analytics to cloud computing and cybersecurity, the demand for tech-savvy professionals continues to soar across sectors.

In-Demand Hard Skills For The New Year

As traditional job roles evolve and new positions emerge, the ability to learn and adapt quickly has become a critical asset in itself. By proactively developing these in-demand hard skills, you not only enhance your marketability but also position yourself to thrive in the face of future disruptions and opportunities in the job market.

1. Artificial Intelligence and Machine Learning

AI and machine learning are becoming indispensable skills in the job market, with their importance growing exponentially across industries. The demand for AI-related skills is 3.5 times higher than the average job skill, reflecting the rapid integration of these technologies in various sectors, a PwC report revealed.

This surge in demand is driven by the transformative potential of AI and ML in the workplace. This fast-emerging technology is expected to automate up to 300 million jobs in the United States and Europe, according to investment bank Goldman Sachs, while simultaneously creating 97 million new roles that require advanced technical skills, as predicted by the World Economic Forum. This shift is not just about job displacement; it’s about job evolution. Companies adopting AI are planning to expand their workforce, with 91% of firms integrating AI aiming to increase their employee numbers by 2025.

2. Cloud Computing

Cloud computing skills will remain in high demand, as the industry continues its explosive growth and transformation of business operations across sectors. Gartner forecasts global end-user cloud spending to reach $723 billion in 2025, a 21.5% increase from the previous year.

The rise of generative AI and the need for integrated platforms are accelerating cloud adoption, with 90% of organizations projected to have hybrid cloud deployments by 2027. As organizations continue to migrate their applications and workloads to the cloud, with 48% planning to move at least half of their applications within a year, proficiency in cloud computing will be crucial for professionals looking to stay relevant in the rapidly evolving job market of 2025.

3. Cybersecurity

Cybersecurity skills are highly coveted, as the digital landscape faces unprecedented threats and skyrocketing costs associated with cybercrimes. By 2025, global cybercrime costs are projected to reach a staggering $10.5 trillion annually, according to a report by Cybercrime Magazine.

This surge in cybercrime is accompanied by a severe shortage of qualified professionals in the field. The cybersecurity job market is expected to grow by 33% between 2023 and 2033, with an estimated 3.5 million unfilled cybersecurity positions worldwide by the end of 2025. This talent gap is further exacerbated by the rapid evolution of cyber threats, with encrypted threats increasing by 92% in 2024 and malware rising by 30% in the first half of the same year.

4. Data Analysis

Businesses are increasingly relying on transforming unstructured data into actionable insights to drive growth, improve user satisfaction and maintain a competitive edge in the market. The demand for data analytics expertise is surging across industries, with trends like AI-enhanced analytics, natural language processing and advanced data visualization reshaping how organizations leverage their data assets.

As organizations grapple with the challenges of data quality and governance, professionals skilled in ensuring data integrity and implementing effective data strategies will be in high demand, making data analysis an essential skill.

5. Digital Marketing

In today’s digital landscape, businesses are leveraging online social platforms to connect with and engage their target audiences and customers.

With global digital ad spending projected to surpass $740 billion in 2024, and over 5 billion social media users worldwide, proficiency in digital marketing strategies will be crucial for professionals looking to thrive in the competitive job market.

Feature Image Credit: Getty

By Jack Kelly

Follow me on Twitter or LinkedIn. Check out my website or some of my other work here.

Jack Kelly has been a senior contributor for Forbes since 2018, covering topics in career development, job market trends and workplace dynamics. His articles often focus on practical advice for job seekers and employees, as well as covering the latest news impacting workers so they can make informed decisions about their careers. Read More

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Artificial Intelligence is Revolutionizing Marketing. Here’s What the Transformation Means for the Industry

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By Jessica Wong

Artificial intelligence technology is changing how marketers reach and engage customers. From programmatic advertising to data analysis, AI can help marketers do a better job, but this rapidly evolving field also raises concerns and uncertainties.

Artificial intelligence (AI) has started transforming every aspect of our professional and personal lives. The marketing industry is not immune to this digital transformation, with leading brands starting to embrace the opportunities the technology brings. Gaining a better understanding of customer behaviour is one of the core benefits of AI in marketing.

For years, marketers have gathered and analysed data about customer behaviour. Their goal has remained largely unchanged — extrapolate patterns and predict which products and services will be most popular with a certain audience. From that basis, marketers would then identify the channels to reach their target customers.

AI is giving marketing professionals an essential advantage in this quest. This fast-evolving digital technology can analyse more data more accurately than humans can. AI and its subfields, such as machine learning (ML), also identify existing behavioural patterns and predict future behaviour based on that.

The growing role of AI in marketing

In 2020, the market for artificial intelligence technologies in marketing was valued at just over $12 billion. While that may seem impressive, it pales in comparison with the global AI market, which was valued at over $325 in 2021. However, the current market size does not reveal the true potential of marketing-related AI. That only becomes clear by considering growth predictions.

According to experts, the market for AI in marketing will exceed $35 billion next year, nearly tripling in size in only four years. Another four years later, in 2028, industry insiders believe that this area of the marketing industry will have tripled once again. Statisticians expect that marketers will utilize AI to a value of nearly $108 million before the end of this decade.

How marketers are using AI today

How realistic are those expectations? Consider this: as of last year, four of five marketing industry experts said they had already included some form of AI technology in their work. When asked to identify the areas in which AI and ML were already enhancing campaigns, marketing professionals named benefits in several areas:

  • Automation of repetitive tasks
  • Analysis of large quantities of data
  • Personalization of campaigns
  • Predicting conversion rates
  • Optimizing the timing of email marketing

Most of those areas benefit the current leading application of AI technology in marketing — programmatic advertising. A recent survey found that 50% of participating marketing professionals named more targeted advertising as one of the main advantages of integrating AI and ML in their approach.

How AI enhances programmatic advertising

Placing the right adverts in front of the right customers at a time when they were receptive to this content used to be a painstaking process. Machine learning algorithms have allowed marketers to automate buying and selling digital advertising space.

Once programmed, the ML algorithms are not static. They mimic human behaviours, including learning. In practice, the algorithm ‘understands’ whether an advert has missed or exceeded expectations and learns from this outcome. There is no need for additional human intervention. The algorithm, or the machine, learns without additional input simply by analysing results and iterating its approach.

Marketers and the brands they represent benefit from improved targeting of specific audiences with customized messages. As a result, conversions grow, and advertising spends more efficiently. Programmatic advertising platforms work by analysing quantities of data that would overwhelm humans.

These platforms cannot only compute data about user behaviour, website analytics, and demographic information. They also see trends and patterns before humans can. Marketing professionals can then use those insights to make their content more relevant, increasing the likelihood of customer engagement. Plus, marketing algorithms can optimize ad placement and bid pricing.

Understanding AI-related concerns in marketing

Like most powerful technological developments, AI has raised some concerns in the industry. In addition, marketers starting to invest in AI technology are dealing with unanswered questions as the technology continues evolving at great speed. Two of the main concerns relate to customers and marketers themselves. These concerns are privacy, data protection and job security in the industry.

Protecting privacy — AI and ML rely on access to large quantities of customer data to recognize patterns and predict potential behaviour. Despite their far-reaching capabilities, these technologies cannot self-police. They will analyse any data fed to them. Marketers need to ensure that their data collection and usage practices are not only ethical. They must also comply with current privacy and data protection legislation, such as the European Union’s GDPR or the California Consumer Privacy Act (CCPA).

Job security for marketers — Job security for marketers is another concern about the growth of AI-based applications. Most recently, these concerns have been discussed in connection with OpenAI’s ChatGPT software. Granted, it is not possible to predict entirely where the marketing industry is headed, but most experts believe that AI and ML will change existing jobs rather than replace them. Marketers can work more efficiently and effectively to benefit the brands they represent. Their daily routine may change, but it is unlikely that robots will replace human marketers anytime soon.

Final thoughts

While AI has the potential to transform the marketing industry as we know it almost beyond recognition, the technology is not here to replace human marketers. Instead, AI and ML can optimize and streamline current marketing approaches.

Both technologies can also take care of repetitive tasks, allowing their human team members to focus on what they are best at and develop creative campaigns that engage more customers than ever before.

By Jessica Wong

Entrepreneur Leadership Network Contributor. Founder & CEO of both Valux Digital and uPro Digital. Jessica Wong is the Founder and CEO of both Valux Digital and uPro Digital. She is a digital marketing and PR expert with more than 20 years of success driving bottom-line results for clients through innovative marketing programs aligned with emerging strategies.

Sourced from Entrepreneur

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2021 predictions: The future digital media technology amidst the pandemic

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Social listening has gained traction in 2020 due to the pandemic, but what is in store for 2021?

Chief Technology Officer Ryan Donovan of Vancouver-based social media management platform Hootsuite and Pierre-Loïc Assayag co-founder and CEO of San Francisco-based influencer relationship management platform Traackr predict that 2021 will be a good year for social business.

The pandemic changed our focus on how we communicate. People relied on social media to stay connected while spending more time at home. Platforms like Twitter, Facebook, and Instagram became lifelines for connecting and maintaining relationships at work and with family.

The pandemic accelerated the move to digital across industries — especially in sales and marketing. Unfortunately, some brands will realize in 2021 they are already too late to the game.

Social commerce and influencer marketing

As budgets shrink and digital becomes more and more crowded, the divide between companies who invested early in social commerce and influencer marketing, and those who have just begun their journey will dramatically increase. In three to five years this will translate directly to market share for digitally-savvy businesses.

The brands that did not use social media to drive customer interactions and sales before the pandemic will be forced to digitize their operations.

Brands that already established a presence on social before the crisis will increase the use of analytics and reporting tools to make business decisions. This will result in brands forming stronger bonds with their customers.

Brand values over price

The most successful brands used social to connect with customers, particularly through one-on-one interactions. Consumers want to see the human element behind the brand and experience real, consistent, and authentic action. In 2021, consumers will increasingly prioritize brand values over price — increasing sales for brands.

Localize data in Europe 

The EU-US privacy battle will force social networks to change. In 2020, the European Court of Justice deemed the EU-US Privacy Shield agreement as invalid, striking a major blow to social networks.

Regionalized networks will emerge

This decision will require substantive changes to social networks and how these platforms operate. Without having the legal right to collect and store data of European users in the US, social networks will be forced to either localize their data in Europe or abandon European markets altogether.

As privacy regulations tighten and the need for social platforms to engage with friends and customers remains, new regionalized networks will emerge to fill the connection gap.

Consumers are now taking steps to protect their personal data online. Instead of giving away an email address or phone number to connect with a brand, consumers prefer to interact with brands via messaging apps.

Research shows that over two in three (66%) consumers prefer to reach brands this way as they interact with their friends and family, more so than by phone or email.

Higher standards of social action

Social media management platforms continue to grow and follow the likes of Facebook by implementing direct messaging capabilities across applications. Businesses will have more meaningful conversations with their customers this way improving customer loyalty. Brands will be held to a higher standard of social action and responsibility.

Social commerce

Social commerce will take centre stage as in-person shopping becomes less viable. Brands will look toward digital with social commerce becoming a key sales channel as it connects customers to brands they trust. The trend is still on the rise, but will soon become a crowded space.

In 2020, social platforms made great strides to advance social commerce offerings during the pandemic. Facebook introduced Facebook Shops and rolled it out to Instagram and Facebook.

Data analysis

Snapchat announced its first shoppable show and Pinterest made it easier for users to find similar products on its platform. In 2021, brands will heavily invest in data analysis to understand the connection between social and sales metrics, further define their KPIs, and inform strategic decisions.

With more than half of the world’s population on social, platforms will focus on developing new features that make it easier for consumers to shop.

Purchases through Instagram or Facebook feed

Advancements in mobile payments will be critical for social commerce. In 2021, Apple Pay and Google Pay will enable consumers to make purchases through their Instagram or Facebook feed.

Digital crypto-currency

Social platforms will experiment with other payment methods like digital crypto-currency, but this nascent e-commerce technology will take place in the background.

Emulating TikTok

TikTok has marked the beginning of a new era by proving the social media platform giants can be challenged with fresh ideas. Starting in 2021, there will be a surge of platforms emulating TikTok with short-form video, low production content, and content-based algorithms for better virality.

With changes in how we communicate, shop, and greet one another, what has become clear is the need for brands to digitally adapt to the new way of working.

With over four billion people around the world using social media each month, social media has played a pivotal role in helping brands fill the void and build customer loyalty during the pandemic.

The challenge for brands is maintaining that loyalty as the world permanently shifts to the new commerce model.

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10 Business Skills for 2021 That You Can Master on Weekends

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Sourced from Entrepreneur Europe

Turn your weekends into a time to learn something new.

In business, you should always be growing. And part of that is learning new skills and trends that are happening in your industry. It’s hard to find time for professional development but with early Black Friday deals on courses in the Entrepreneur Store, you might be able to work something out. We’ve rounded up some of the top deals on online classes available now, and you can get all of them for an extra 15 percent off when you use code SAVE15NOV at checkout.

Running a Shopify store.

Have something to sell? Then you need to be on Shopify. In this 30-hour guide to SEO, drop shipping, design, branding, and more, you’ll learn how to build a Shopify empire with help from the experts.

Get The Complete Shopify Bootcamp Bundle for $25.50 with promo code: SAVE15NOV.

Data analysis

Data analysis helps businesses make more informed decisions and grow with greater purpose. It’s important that any aspiring entrepreneur knows how to work with data. In this 29-hour bundle, you’ll dive into Excel, Power BI, Python, and more tools to manipulate and analyse data effectively.

Get The 2021 Advanced Data Analyst Bundle for $25.50 with promo code: SAVE15NOV.

Social media marketing

Grow your business on social media with help from this massive boot camp. With more than 34 hours of training in Facebook, Instagram, and LinkedIn marketing, you’ll learn what it takes to stand out from the noise on every feed. There’s even a course dedicated to building a complete social media strategy.

Get The 2020 Social Media Marketing Bootcamp Certification Bundle for $25.50 with promo code: SAVE15NOV.

Designing and editing in Creative Cloud apps

The Adobe Creative Cloud is the top creative suite on the market. In this eight-course bundle, you’ll get 60 hours of training in Photoshop, Lightroom, Illustrator, After Effects, and more. Before you know it, you’ll have professional-grade design expertise.

Get The All-in-One Adobe Creative Cloud Suite Certification Course Bundle for $28.90 with promo code: SAVE15NOV.

Selling with Amazon

Amazon is the country’s largest marketplace for one major reason: It makes it easy for anyone to sell on their platform. Fulfilment by Amazon (FBA) is Amazon’s dropship program that helps independent sellers earn money through Amazon. This course will teach you how to use this industry monster to earn passive income.

Get The Ultimate Amazon FBA & Dropship Master Class Bundle for $34 with promo code: SAVE15NOV.

Financial analysis

Certified financial analysts (CFAs) earn the big bucks to help individuals and businesses manage and grow their finances successfully. As you might expect, to get into this career, you need some pretty unique knowledge. This training will prepare you to ace the entry-level CFA certification exam on your first try.

Get The All-In-One CFA Level 1 Exam Certification Prep Bundle for $34 with promo code: SAVE15NOV.

Accounting

Accounting is hard, which is why individuals and businesses alike pay accountants to manage their finances. In this course, you’ll learn accounting from CPA Robert Steele, so whether you want to handle your own finances better or become a professional accountant, you’ll have the skills you need to succeed. From financial statements to calculating depreciating assets, you’ll get a comprehensive accounting education.

Get The Ultimate Financial Accounting & CPA Certification Training Bundle for $38.25 with promo code: SAVE15NOV.

Google Ads and search engine optimization

Google is the world’s largest advertising platform, facilitating both paid and organic opportunities for digital businesses. But it’s one thing to advertise on Google, it’s another entirely to build your website to be fully SEO-optimized. In this course, you’ll learn how to optimize your website for organic traffic, and grow traffic through paid efforts.

Get The Ultimate Google Ads & SEO Certification Bundle for $42.50 with promo code: SAVE15NOV.

Project management

Efficiency is everything in modern business, especially in today’s economy. In this ten-course bundle, you’ll learn how to complete projects on-time and under-budget with help from today’s top tools and tech. You’ll explore Scrum, Agile, PMP, and more.

Get The Project Manager’s Essential Certification Bundle Ft. Scrum, Agile & PMP for $42.50 with promo code: SAVE15NOV.

Computer programming

If you want to learn to code, there’s no better resource than this bundle. Across 27 courses, you’ll get more than 270 hours of training from top-rated instructors like Rob Percival and Nick Walter. You’ll cover web and app development, machine learning, software engineering, and much, much more.

Get The Premium Learn to Code 2021 Certification Bundle for $51 with promo code: SAVE15NOV.

Feature Image credit: Nathana Rebouças 

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What Is The Difference Between Data Analysis And Data Visualization?

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By Eva Murray

The two terms data analysis and data visualization seem to have become synonymous in everyday language in the wider data community.

Numerous job adverts focus on data visualization skills while not necessarily specifying the importance of analytical skills. Job titles reflect this trend with the emergence of new roles such as ‘data artist’, ‘data visualization expert’ and ‘data storyteller’, but organizations are still looking for people who can extract value from their data, so these roles must include analytical skills.

Data Analysis versus Data Visualization

Data analysis is an exploratory process that often starts with specific questions. It requires curiosity, the desire to find answers and a good level of tenacity, because those answers aren’t always easy to come by.

Data visualization involves the visual representation of data, ranging from single charts to comprehensive dashboards. Effective visualizations significantly reduce the amount of time it takes for your audience to process information and access valuable insights.

Visual analytics in the process of analysis

However, that’s not to say that the two never work in harmony – far from it. In working with data, analysis should come before the visual output, but visual analytics can be an excellent method for running more effective analyses.

Visual analytics involves the process of building different charts with your data to give you various perspectives. This helps you identify outliers, gaps, trends and interesting data points that warrant further investigation.

The process of analysis is similar to the design process depicted through ‘the design squiggle’ by Damian Newman.

The Design Squiggle

Damian Newman

On the left you have the process of analysis, research and visual exploration which turns into more clarity, an understanding of the data and the finding of insights as you move to the right. Only at the conclusion of the process comes the dashboard, the output that brings everything together in a neatly packaged output.

What is the role of a dashboard?

In your job as a data analyst or visualization expert you will likely be creating dashboards for your stakeholders. What is the role of the dashboard in the entire analytical process, though?

Many people see it as the ultimate deliverable that will answer all their questions. I suggest, however, that the dashboard is just a starting point for further discussion and analysis.

A dashboard, infographic or data story can be an excellent and very effective method for communicating insights. It shouldn’t stop there, though. At the point when your stakeholders work with their interactive dashboard, printed PDF report or the screenshot they have received by email, that is when further discussions should come about. It shouldn’t be the end point.

Look at the below Sales & Profitability dashboard created by Ann Jackson. It is a visually compelling, cleanly designed summary of the data that shows the changes over time, the geographical differences, losses for certain product categories and summarizes key performance indicators as numbers.

Sales and profitability by US state Ann Jackson

Would Ann hand this dashboard over to her stakeholders and call it done? No, because now the real discussions start. Ann can sit with her audience and drill into further details to explore why certain results have come about and identify opportunities for improving business performance. Further investigation of the data, exploring it with your audience, that is the value you add as an analyst, beyond producing dashboards. They give you an excellent basis for these discussions but shouldn’t be the end point.

Don’t stop at the visual

One piece of advice I have shared with many analysts in the wider community is to not simply visualize data, but to show insights and to demonstrate your analytical skills.

Many tools make it very easy to build visualizations quickly. Your role as an analyst is to ensure that the information they present is accessible, easy to understand and clear. I strongly encourage you to put your findings into actual sentences, annotations, titles and subtitles to guide your audience through your report or dashboard and make information accessible, regardless of their level of data literacy.

Ask yourself the question: are my conclusions easy to understand for someone who didn’t go through the same analysis and research process with this dataset?

Look at this visualization by Justin Davis. Justin created two charts and supported them by stating his findings in text. He could have stopped at using titles for each chart, but the inclusion of three sentences ensure that his audience doesn’t have to do their own analysis first and can instead understand quickly what the data shows. And then, they can ask further questions.

The number of women in the House has increased over the last 50 years Justin Davis

Another great example comes from Jenna DeVries who created a simple visualization of Major League Baseball beer prices.

Adding annotations throughout the visual to help her audience understand key findings makes the information accessible and also shows that Jenna didn’t just create a chart but rather went through a process of analysis which resulted in a visualization that best presents her conclusions.

Beer prices in the MLB Jenna DeVries

Show your analysis

Data analysis and data visualization may be different activities, but they’re intrinsically linked, and one can usually support the other.

When you work with data and build your next dashboard, I encourage you to give additional thought to how you can more effectively incorporate your findings. How can you show the key insights to your audience in a way that is most accessible to them?

An effective, well-designed visualization is great but you risk losing your audience if the information is hidden in data art and cannot be acted upon by your stakeholders.

Feature Image Credit: Pixabay

By Eva Murray

I lead the Business Intelligence department at Exasol, provider of the world’s fastest in-memory database. I‘m responsible for executing the company’s data-driven strategy. I am one of Tableau’s Zen Masters, sitting with 29 other world-leading data experts. My passion is bringing data to more people, using it to help change lives, creating educational content and collaboration opportunities for data professionals across the world. I have co-authored a book about Data Analysis and Visualization best practices and co-host the weekly social data project #MakeoverMonday, which connects data professionals around the world. I also run weekly webinars and collaborate with industry experts to create content for data analysts, data scientists, and data storytellers. Initiatives such as #Data+Women and #WomenInTech are important to me, so I work to connect people with the right opportunities for their career progression and development. Outside of work, I’m a passionate triathlete and I love to travel.

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Three Data Technologies To Make 2019 Your Best Year Yet

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By Shant Hovsepian

Gartner recently released its list of top 10 strategic technology trends for 2019. It’s an intriguing list, and we can glean from it where disruptions of the future might occur. There is a common thread that holds each of the trends — artificial intelligence (AI), augmented analytics, blockchain and more — together: the ability to turn data into a business asset. That future growth lies in the ability to turn data into something useful isn’t a surprising revelation. But not every organization is equipped to make the most of its valuable information.

Business leaders who wish to move their companies in 2019 with swift efficiency should look to the following three mechanisms for turning data into value.

Enable Search-Based Business Intelligence (BI)

Gartner defines search-based discovery tools as those that “enable users to develop and refine views and analyses of structured and unstructured data using search terms.” As organizations become increasingly preoccupied with leveraging data for gains in operational efficiencies, the ability to easily access that information becomes paramount. The idea of using a Google-like interface for BI has been around for a while. Yet despite the ease with which we open a browser and search for things we want on a daily basis, that same, simple interface for accessing data sets isn’t always available in the enterprise.

The original search engines launched in the 90s (hello, Lycos) were the first public displays of big data in action. Over the years, the high-tech industry has sought to build a similar environment, where corporate users realize, economically, scale and processing power for big data analytics. As many of us now know, most of the tools required to replicate that type of big data environment are available today. It’s interesting, then, that with so much emphasis on big data analytics, that using a Google-like interface in the enterprise is still restricted to small segments of the available data sets.

The pursuit of making big data analytics easier for all users must be a cornerstone of organizations’ 2019 philosophies. And it likely starts with identifying the right underlying technologies. Just as public search engines had migrated their architectures from using “big iron” to using distributed computing on commodity hardware, organizations must identify the right architectures for getting value from search-based BI across all their data. That might ultimately help them to figure out how to approach analysis the same way we approach figuring out where to go to lunch.

Tame The River Of Streaming Data

The internet of things (IoT) emerged as a buzzword not long ago, but we seem to be past its apex and into its post-hype cycle. The thing is, it’s still a hot topic, and there are still likely to be over 30 billion IoT devices by the end of this decade. The data they produce must go somewhere. It’s not even just the fabled IoT-device deluge that is causing proverbial data streams to overflow. Things like website clickstreams and financial market data also take the form of rivers through an analytics infrastructure. The trick is to drill into the most important parts and turn them into something valuable.

There are two main objectives that organizations must achieve to get the most out of streaming IoT data. The first is defining how to deliver insights immediately in order to take immediate action and leverage a recent event. While automation typically lends itself well to taking immediate action in real time, there are many scenarios that require human input. One example — operations optimization — might require a system to detect events indicating an inefficiency or error. The second objective is to provide a user interface that a broad, typically non-technical audience can use. IoT analytics is often seen as a technical domain with data scientists and data engineers leading the way, but with a limited talent pool, organizations must enable, with the right tools, business users to find insights in streaming data.

Visualize Your AI

We hear a lot about athletes using the tactic of positive visualization. “Visualize your swing before your next at-bat.” It’s a way for those in their peak physical power to link mind with body.

With the tools at the disposal of organizations today, it’s time that business leaders took a similar tack with their approach to 2019’s data strategy. Artificial intelligence (AI) has emerged as a high-priority technological pursuit today, but there’s a risk that AI is only used in the domain of highly technical personnel. With a strategy around visual analytics on AI, you can have more types of users understand outputs from AI-driven analysis, such as capturing customer sentiment, streamlining business operations and predicting upcoming problems.

The key objective with enabling visual analytics on AI is to open that capability to everyone, including the non-technical business users. Chances are, your organization doesn’t have time to wait for a data scientist to respond to requests for analytical outputs. You need the insights from your data now, and you need the people directly responsible for acting on those insights, regardless of job role, to be able to open a dashboard and understand what’s happening based on the work of your data scientists. Chances are, you’re unlikely to get far if the best means of communicating analysis is through a complicated spreadsheet. A sheet filled with numbers isn’t for everyone but user-friendly charts, graphs and dashboards are.

This Holiday Season, Give Data Analysis To Everyone

2019 is around the corner, and that means your data strategies should be in tip-top shape before the holidays arrive. At the heart of your holiday giving plans should be providing access to big data analytics to everyone in your organization. Only when business leaders truly democratize their organizations’ data analytics can they enjoy the benefits that big data offers. Search interfaces, streaming analytics and visual analytics aren’t the only ways to make data available to everyone, but they should be strong considerations. Data is the key to a competitive edge, and it’s time to turn that information into insight, today.

Feature Image Credit: Getty

By Shant Hovsepian

Shant Hovsepian is a Co-Founder and CTO of Arcadia Data, he is responsible for the company’s long-term innovation and technical direction.

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The Five Most In-Demand Skills For Data Analysis Jobs

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By Jeff Kauflin ,

Data and statistics seem to be making their way onto every avenue in the workforce, and there are hundreds of programming languages, tools and methods for practicing the craft. But which skills are in highest demand in the job market?

Trilogy Education, a New York-based startup that partners with universities to offer continuing education classes in technology, did research to identify the most in-demand skills for data analysis jobs. Trilogy works with 24 universities, such as Berkeley, Northwestern, and UNC Chapel Hill, to teach classes on web development, data analytics and online user experience. For the research, Trilogy used a database created by job analytics firm Burning Glass. It looked across more than 25.6 million positions, evaluating the number of times specific skills appeared in descriptions for jobs across the country.

1. Data Analysis

No, seriously, data analysis is the most in-demand skill. Granted, it’s a strange one to appear on a list of the same name, but Trilogy defines it as the critical-thinking ability to interpret numbers. “It’s the ability to tell a story that gives insight into a problem,” says Dan Sommer, Trilogy’s founder and CEO. In other words, in addition to knowing how to use specific programming languages and tools, employers need you to discern when patterns in data are meaningful, so that you can draw accurate and actionable conclusions.

2. SQL

SQL, the second-most in-demand skill, is a programming language used to retrieve information from a database. It was first developed in the 1970s and is ubiquitous. If you want to be a business analyst, data analyst, data engineer, data scientist, web developer, software engineer or database administrator, it’s important to know SQL, Sommer says.

3. Data Management

Data management relates to how you structure databases, which can have complex rules around who can access different pieces of information. And there are different approaches to storing data as efficiently as possible. A common job requiring data management skills is database administrator.

4. Business Intelligence

Business intelligence is the practice of gathering data to inform business decisions. For example, a company using direct mail and Facebook ads to market its products can use business intelligence software to help understand how well each marketing tactic is working. Business analyst, business intelligence developer and customer insight analyst are a few jobs requiring business intelligence skills.

5. Data Warehousing

“Data warehousing is the process of combining large amounts of data (usually from disparate sources) into one place to enable analytics,” Sommer explains. Companies today often have large amounts of information coming from different places, and a data warehouse lets it all sit in one happy location. A common data warehousing job is data engineer.

Image Credit: Shutterstock

By Jeff Kauflin ,

Follow me on Twitter @JeffKauflin or email me at jkauflin[at]forbes[dot]com.

Sourced from Forbes

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