paint-brush
Data and Analytics Predictions for 2020 [A Top 5 List]by@pradyut-hande
597 reads
597 reads

Data and Analytics Predictions for 2020 [A Top 5 List]

by Pradyut HandeJanuary 12th, 2020
Read on Terminal Reader
Read this story w/o Javascript
tldt arrow

Too Long; Didn't Read

Data and Analytics Predictions for 2020 [A Top 5 List] are based on data and analytics trends. Data scandals have opened a can of worms for the industry, which now everyone has to deal with. Big brands kept galloping to pivot to the privacy-first model with CCPA and GDPR coming into effect. Marketing teams will need to carefully assess their third-party data vendor ecosystem to ensure they don’t face any lawsuits. Companies with shoddy data ethics will face the loss of reputation, consumers, and employees.

Companies Mentioned

Mention Thumbnail
Mention Thumbnail

Coin Mentioned

Mention Thumbnail
featured image - Data and Analytics Predictions for 2020 [A Top 5 List]
Pradyut Hande HackerNoon profile picture

It would be no exaggeration to say that the capacity of technology to advance itself is proceeding at a faster rate than our ability to process these changes all at the same time. This is both amazing and alarming in the same breath. 

And if there’s one space in marketing where we saw the most changes because of technology in 2019, that’s data and analytics. 

Businesses are literally flooded with data. There’s so much of it that we struggle to know what’s important, and what’s not. However, it still remains a “good-to-have” problem. The bigger challenges, however, are presented by the increasing privacy and safety concerns. Data scandals have opened a can of worms for the industry, which now everyone has to deal with. 

Much of the trends and predictions for 2020 that we see are centered around dealing with these challenges. Some of them are technology-oriented while others are non-technological in nature. 

Let’s talk more about them in detail:

1. Understanding Data Legislations and Protecting Customers

2019 was an eventful year for data privacy. It rained lawsuits. Consumer privacy concerns occupied space in both key courts and state legislatures as well as in Silicon Valley. It all started with the Facebook-Cambridge Analytica scandal in 2018 and soon other technology giants like Amazon, Apple, and Google faced litigations too.

For the most part of 2019, big brands kept galloping to pivot to the privacy-first model. With CCPA and GDPR coming into effect, this has become a must for every business running operations online.

If you check your inbox, you will already find plenty of emails with titles like “Privacy Policy Updates”, and “Terms of Services and Privacy Update”. These are businesses scrambling to safeguard themselves from heavy fines and potential loss of reputation in the future. 

In 2020, marketers will continue to re-analyze the consumer data they already have. Everyone in the marketing team will need to understand how their business collects, processes, and stores data. There was a time when ignorance was bliss, but marketing in 2020 won’t give you the same luxury. 

Besides, the current state legislations are expected to evolve further as the technology companies and consumers will continue the conversation in the courts. We will see different definitions of privacy, private information, and privacy breach – each varying from one legislation to another. For example, even if you are GDPR-compliant it may not mean that you are covered for the CCPA too. 

New federal legislatures may also come into being. Staying informed about every single update would have never been as crucial as it will now be. As for compliance, we will see brands spending a lot more than before on consultants and systems. B2C businesses are likely to find it more challenging and may struggle to retain user data for marketing and advertising purposes. 

Marketers will need to carefully assess their third-party data vendor ecosystem to ensure they don’t face any lawsuits, which are expected to increase by 300% in 2020. Because of increasing customers adopting anti-surveillance technologies to thwart government surveillance, businesses are also set to lose access to customer data like IP addresses, location, facial data, etc. Companies with shoddy data ethics will face the loss of reputation, consumers, and employees. 

In 2019, as per an IBM research conducted by the Ponemon Institute, the average cost of data breaches was around $3.92 million. In fact, the total number of data breaches increased by 54% in the first half of 2019. 

Companies will attempt to collect and weaponize data through M&A activity. The cost associated with deep-fake scams will exceed $250 million. Companies will avoid sharing their data with third-party vendors. One in five enterprises will safeguard data from AI.

As the ramifications of data breaches become even more serious, securing data against insider threatsexposed databasesphishing scamsransomware attacks, and many more will become the ultimate priority for businesses. 

All this is set to keep marketing teams on their toes throughout 2020. Brace yourself! 

2. Natural Language Processing and Conversational Analytics

If there is a trend that is going to be truly revolutionary for data analytics, it is going to be NLP (Natural Language Processing) and conversational analytics. NLP and conversational analytics eliminates the need to program queries for advanced analytics.

It now allows humans and computers to interact using natural language, making data accessible to a larger pool of users. 

Natural Language Processing has always been one of our science fantasies. Remember HAL 9000 from Stanley Kubrick’s “2001: A Space Odyssey”? To date, it’s considered an iconic moment when HAL says, “I’m sorry Dave, I’m afraid I can’t do that.” This was in 1968. It definitely took us some time to reach where we are but NLP has finally established itself as a developed branch of artificial intelligence.

Google is already using it to make the internet accessible to everyone. Now the next is businesses that will find it easier to ask questions about data and receive an explanation of the insights. Conversational analytics will take it to a whole new level by processing questions and answering verbally instead of using text. 

Gartner is optimistic about its outlook on the future. It foresees that NLP and conversational analytics will boost the adoption of analytics and business intelligence among employees from 35% to over 50% by 2021. Among those who will adopt it will be a whole new class of users like front-office workers. 

3. Augmented Analytics Making It Easy to Understand Data

Gartner included Augmented Analytics in its Hype Cycle for the first time in 2017. In its report, it described Augmented Analytics as “the next wave of disruption in data and analytics.” Unarguably, it turned out to be so and dominated the data landscape in 2019. 

Augmented analytics has proven to be a remedy to the time-intensive process of analyzing and interpreting data. The technology is essentially aimed to empower non-technical/non-data scientist users to be able to perform analysis on their own. It also relieves data scientists from having to choose the right algorithms and write a code to get the data. 

It combines both the power of machine learning and NLP (Natural Language Processing). Augmented analytics tools are capable of handling large sets of data and are able to integrate well with analytics platforms, saving a lot of time.

The interesting part is that these systems will be able to interact with data organically, on their own. They will also surface any unusual trends and report them to businesses. 

Gartner predicted in its 2019 report that, “By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence.” Grabbing the top spot in several industry trends reports, augmented analytics is sure to make waves in 2020.

4. Unified Data to Connect all the Dots

Businesses run different applications and use varying technologies for different business purposes. All this has resulted in a massive amount of data that can be structured, unstructured, and semi-structured. Since this data is siloed across a diverse set of data sources, it also causes silos in teams and different business units. 

Without having a central system to manage all the data, you can’t have accurate insights. And this often results in uninformed or poorly informed decisions. But when you are able to unify your data, you become better equipped to plan, forecast, budget and build products and services. 

Last year, we saw Google coming up with a unified data solution for app and web analytics. The company combined the capabilities of Google Analytics and Google Analytics for Firebase (for mobile apps). It was a much-needed solution. More and more technologies are expected to crop up to help businesses build a single source of truth for all functions. 

In 2020, you will see more and more businesses using technologies for breaking data silos. In fact, most of the marketing in the future would require businesses to have a unified view of their customers. More than ever, it has to be seen more like a ‘must’ rather than an ‘option’. 

5. Innovation in Data Storage and Management Technologies

Up until a few years from now, most companies stored and processed their data using their own captive data centers. This changed with the onset of cloud services and thereby, resulted in hyper-scale cloud companies. These solutions allow businesses to not only reduce costs but also increase profits. 

The public cloud market, comprising of cloud applications (SaaS), development and data platforms (PaaS), and infrastructure (IaaS) services combined, is predicted to grow to $299.4 billion by Forrester. We will see a slow but healthy CAGR of 21%, and this growth will lead to more demand, spending, and development of enterprise data solutions. 

Hyper-scale global public cloud leaders will form more alliances while refocusing on their core strengths. Leading business app vendors will ditch their proprietary infrastructures.

High-performance computing will take off. The crowded cloud-native development ecosystem will deliver service meshes and serverless computing, and cloud management vendors will shift focus to security after a well-publicized public cloud data breach.

We will also see artificial intelligence and machine learning increasing their penetration in enterprise-level data management solutions.

According to Gartner, “with technical skills in short supply and data growing exponentially, organizations need to automate data management tasks. Vendors are adding machine learning and artificial intelligence capabilities to make data management processes self-configuring and self-tuning so that highly skilled technical staff can focus on higher-value tasks.” 

The trend is set to give rise to augmented data management and impact the complete ecosystem such as “data quality, metadata management, master data management, data integration, and databases.”

Conclusion

It surely becomes overwhelming if you think about the mere scale of challenges in front of us. But, there’s always a way out. 

For businesses to be able to take steady steps towards growth and right decisions, a clear vision that is both meaningful and actionable is needed. This will be required to view the ecosystem as a whole (both the technological and non-technological aspects) that we have in place right now.

Gartner’s Neil Osmond also cautions us to the overuse of the word “change”. He advises businesses to avoid falling into the trap of “transformation fatigue”. Quoting him, “People come to work to deliver, not to change. If you’re forcing change on them, it can be really tiresome.”

Start with talking to your teams first. Help them understand your vision and connect with it. To build trust and confidence and drive actual change, create a clear plan they are able to understand!

(Originally Published here)