Disrupt or be disrupted. As the data-driven landscape evolves – businesses today are becoming increasingly aware that data-driven companies are thriving. 2020 will be the year where true data driven organizations separate themselves from the competition – powered by real-time decision making, advancements in analytical technologies and increasing data literacy among business users. Listed are ten data analytics trends to watch heading into 2020.
Renewed Focus On Data Culture
Nothing good ever comes easy. 80% of Chief Data Officers claim that fostering a data driven culture is one of their greatest challenges – spending a vast majority of their time evangelizing for data transformation. 2020 will be the year of a renewed commitment to building data driven cultures and empowering the business through data-driven decision making. Expect companies to invest in programs, training and side-side consulting that will increase business user’s data literacy and ultimately the overall trust of their data.
Agile Data Becomes Standard
Businesses will demand better and more real-time analytics in 2020. An agile data framework and the ability to “fail fast” and pivot in real-time is critical to the livelihood of data driven
businesses. A consumption-based architecture begins with the specific business’ needs and delivers value over a series of agile sprints designed to unlock the data and empower the business. CIO’s will increasingly seek out systems and frameworks that produce real-time insights. A traditional data warehousing approach, while it has its place, often fails to address the continuous changing needs of the business and the agility to pivot in real-time.
IT Embraces Self-Service
We’ve debated and fought the idea of Self-Service Analytics for decades. This will be the year when IT Departments embrace self-service and openly work with the business to create accessible data silos where IT can still implement governance and security. Considering
the sprawl of Excel workbooks on desktops all over the world, this seems like a victory for all parties. The evaluation of cloud-based data automation tools has allowed IT to spend more time understanding business needs and designing a solution that works for everyone.
Birth of Citizen Analyst
2020 will become the year where analysts actually get to analyze something. How many organizations have an analyst who spends 80% of their time cobbling together Excel reports to copy, pasting into Power Point, and sending to executives on a monthly basis? This approach has become detrimental to companies and this individual’s career. The advent of the “Citizen Analyst” changes that. The business intelligence tools exist today to automate the data wrangling, data modeling and analytics. Thus, allowing your analyst more time to uncover key trends and explore prescriptive analytics that drive your business.
Prescriptive Analytics
Data driven transformation will focus on taking action. 2020 will be the year when companies implement frameworks, methodologies, and change-management architecture to truly take action on the insights they uncover. The ability to move from Descriptive Analytics (what
happened) to Prescriptive Analytics (what action to take) is a gap in many organizations. In the past, too many companies had the ability to uncover critical insights but were left paralyzed by the inability to action on these insights. Expect organizations to invest in data focused Business Consultants with deep industry expertise who can implement actionable frameworks and facilitate data driven decision making across an organization.
“Companies are generating more data today than at any other point in human history”
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Wealth Creation
Data is the new oil – and many are suggesting it’s the world’s most valuable resource. Companies are generating more data today than at any other point in human history. In the New Year, businesses will continue to focus on accumulation of data assets and leveraging cheap cloud storage options like Data Lake. Companies that get their data right in 2020 – will pave the way to the industrial revolution. Data is the fuel and the engine for the AI Revolution. Collecting data assets today, and holding, will allow organizations to cash in when it counts the most.
AI Revolution
Widespread adoption of Artificial Intelligence will not happen in 2020. The AI Revolution is coming, but widespread adoption is still a couple years away. The technology exists today. Even the CSI facial recognition AI that we never thought was possible. Blockchain, 5G mobile and data privacy technologies need to mature before robots begin taking our jobs. AI headlines every article we read today – because it tugs at our heartstrings of curiosity and generates clicks. Companies still need to further embrace cloud platforms and modern data analytics practices before AI becomes widespread. With that said, we will continue to see augmented analytics and AI built right into our everyday technology platforms. Alexa tell me a joke…
“Blockchain, 5G mobile and data privacy policies need to mature before robots begin taking our jobs.” ”
Data Scientist FOMO
Bitcoin ballooned two years ago as consumers developed a Fear of Missing Out (FOMO). Data Scientists will again be all the rage in the New Year as organizations decide how to respond to their FOMO. Many organizations are ill equipped to fully maximize the talents of a true Data
Scientist. Furthermore, they will struggle to quantify the ROI of their investment. Advanced algorithms and machine learning are great in and of themselves but difficult for companies to embrace who haven’t first established a data driven culture. LinkedIn reports a 56% increase in Data Science job postings since 2018. This won’t prevent companies from hiring Data Scientists – rather it will challenge Data Scientists to become evangelists for data transformation and justify their own ROI to individual business segments. The most impactful Data Scientist will be the one who has deep industry expertise and will possess the ability to open lines of communication with the business.
Data Silos vs. Data Farms
Rethinking your data strategy requires rethinking the role of a traditional data warehouse. Architecting a data fabric built upon data silos allows your data to be more distributed and an agile functionality to meet the business needs. With this consumption-based architecture, there is a distinct purpose for the data silos, data lake, data barn, the tractor shed, old root cellar and that drainage pond out back. Perhaps a Data Farm is a better description. A modern
data fabric architecture that is optimized for the business to seamlessly access the assets they need to operate the business daily. Gartner forecasts that through 2022, custom-made data fabric designs will be deployed as static infrastructure and support agile data at scale. Forcing a new wave of dynamically resigned approaches to data success.
Business Intelligence 2.0
Business Intelligence traditionally has provided a historic look at a business. The term Business Analytics is used today to provide a view of the past, present and the future. 2020 will be the
year companies look past simple data visualization and embrace data storytelling, natural language processing, real-time embedded and mobile analytics capabilities. We aren’t far off from a CFO holding his mobile device and asking, “what was the sales revenue for last month”. Swiping over to view a data story summarizing the current month with live data tiles. Simple yet powerful analytics that don’t require a Data Scientist. More companies large and small will embrace a modern approach to consuming their data and uncovering insights.
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Robert Gerads is CEO of Fulton Analytics, a data analytics strategy and consulting firm based in St. Paul, MN. He is also the founder of the Twin Cities Power BI Meetup.