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Data Science & Analytics Predictions, Trends, & Forecasts

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The world of data science is expanding as new technologies and use cases push innovation to meet the rising demand for data-driven business outcomes. 

2022 promises several nascent and growing data initiatives across segments of the market and within enterprises. 

Read on to learn what a group of experts predict we can expect in data science and analytics in 2022:

9 Data Predictions for 2022

  1. Addressing growing data quality concerns
  2. Investing in remote worker cybersecurity and threat detection
  3. The growth of natural language processing
  4. Commodifying the Internet of Things for real business needs
  5. Leaning on AI for network monitoring
  6. Data fabrics aiding the management of unstructured data
  7. Tech workers demanding new benefits
  8. Shifting cloud security landscape
  9. Localization meets globalization in data compliance

Also read: Big Data Trends in 2022 and The Future of Big Data

1. Addressing growing data quality concerns

Everything from machine learning (ML) models to network security monitoring tools to enterprise resource planning (ERP) software requires access to large pools of big data.

And while many organizations have been collecting and finding the data they need to fuel these tools, they have not always placed data quality management at the forefront of their priorities. 

2021 was one of the first years when data quality improvement started to receive focus, but still, many organizations do not feel confident that their data is clean or usable.

Tendü Yogurtçu, CTO at Precisely, a global leader in data integrity, believes that data quality initiatives will not only continue in the new year but will grow as many organizations expressed concerns about the operationality of their data in 2021. 

“Data quality and data integrity will continue to be major focuses for organizations in 2022,” Yogurtçu said. Organizations are becoming more data-driven, which seems obvious, but now the pressing need is ensuring the quality of that data over quantity. 

“And while most enterprises have established a basic foundation for data-driven decision making, they also report struggles with achieving data integrity at scale. In fact, 80% of chief data officers surveyed by Corinium have data quality issues that interfere with integration.

“Businesses will enrich their data by adding context from third-party data and eliminating data silos, allowing better quality data for their organization.”

Learn about data analytics trends: Top Data Analytics Trends

2. Investing in remote worker cybersecurity and threat detection

A number of companies have permanently or semi-permanently shifted their teams to remote work. 

There are definite pros and cons to this workplace shift, with one of the most crucial drawbacks being the limited network security infrastructure and visibility when workers are on their home networks and personal devices.

Brian Robertson, senior product marketing manager for RSA NetWitness, a top security information and event management (SIEM) and extended detection and response (XDR) security solutions provider, believes there are several key threat detection technologies and techniques that can help companies improve their remote worker security posture and reduce their risk of a cybersecurity breach.

“Many organizations are now supporting remote work, so now cybercriminals are finding ways to exploit that through either infiltration techniques or ransomware,” Robertson said.

“There are multiple approaches to address this, but a couple seem to be gaining a lot of momentum. The first is extended detection and response, and the second, which some look at as complimentary to XDR and some view it as part of XDR, is SOAR.

“XDR is designed to detect threats, regardless of where they live, by using endpoint and network data and applying advanced analytics to it. We also feel that XDR should incorporate vast threat intelligence and leverage automation and orchestration to act against identified threats.

“SOAR is designed to leverage vast threat intelligence to identify threats, and those threat intelligence sources can be open threat feeds, subscription threat feeds, industry intelligence, and even crowd-sourced intelligence. However, having all this intelligence is only useful if you can take direct and focused action against it, either by orchestrating activities across the security team or through automation performed by an orchestration and automation solution.”

Learn about cybersecurity trends: Top Emerging Cybersecurity Trends

3. The growth of natural language processing 

Natural language processing (NLP) is continuing to take new shapes as different businesses discover valuable applications of artificial intelligence (AI) technology. Several experts believe that NLP will grow across industries in the next year. 

Ali Siddiqui, chief product officer at BMC, a large IT consulting and services firm, said more companies will recognize the value-add of NLP-driven customer service bots in the near future.

“We can expect natural language processing to grow in the future,” Siddiqui said. 

“Chatbots built on NLP improve efficiency and provide better customer experiences. They provide fast, relevant answers and streamline communication by closing feedback loops and improving productivity gains, allowing employees to spend time on more meaningful tasks.”

Ranjan Goel, VP of products at LogicMonitor, a cloud-based infrastructure monitoring platform, said NLP has started and will continue to help with unstructured data and security management.

“Natural language processing has advanced significantly in consumer use cases and is now moving into enterprise products to help with unstructured data,” Goel said. “It’s enterprise use cases vary, including finding anomalies in the logs, cluster logs, and alerts.”

Jean-François Gagné, head of AI product and strategy at ServiceNow, an IT service management (ITSM) and service desk software provider, said low-code/no-code applications are starting to be developed through natural language interfaces.

“Fundamental research in text to SQL is paving the way for software applications to be built through natural language interfaces, without the need for any knowledge of how to write code,” Gagné said. “A user describes the application they want to an intelligent chatbot, along with the data to use for training, and AI can take care of building the application on the fly.”

Learn about artificial intelligence trends: Artificial Intelligence Trends & Predictions

4. Commodifying the Internet of Things for real business needs

Many Internet of Things (IoT) developers and customers have explored different IoT applications for a while now, but piecemeal IoT engagement has not driven true business gains for most users. 

Some experts predict now that many companies are comfortable with the basic idea of and need for IoT, they’ll begin to truly strategize how IoT can meet their business goals.

Vishal Gupta, chief information and technology officer at Lexmark International, an IoT and cloud imaging solutions company, believes many organizations, including those that do not have in-house IoT expertise, will find ways to create actionable IoT products that optimize their existing products and services.

“I view IoT innovation as being more integrated to key business outcomes,” Gupta said. “Until now, there has been a mentality to push technology forward, even if the results didn’t necessarily produce any tangible benefit for the business. In other words, innovation for innovation’s sake. 

“The problem, as identified by McKinsey, is that a majority of these IoT experiments, 84%, to be exact, get stuck in the pilot phase. The foundation already exists with cloud, 5G, artificial intelligence, and machine learning. With the pandemic, there is a pressing need to make IoT matter.

“In 2022, organizations who cannot build their own IoT solutions will partner with experts — in software or services — to start realizing predictable, repeatable, and measurable outcomes. If they don’t, they risk falling behind.”

Learn about IoT trends: Top Internet of Things (IoT) Trends: The Future of IoT

5. Leaning on AI for network monitoring

Artificial intelligence use cases have grown across industries in process automation, cybersecurity, and customer service, to name a few. 

But AI has typically been used as a supportive technology for legacy solutions, like workflows, campaigns, and dashboards. Few companies have used AI to completely replace these technologies.

Jeff Aaron, VP of enterprise marketing for Juniper Networks, a top global networking company, believes that 2022 may see AI take over standby technologies in network monitoring, such as administrative dashboards. 

“AI-driven assistants will largely take over the monitoring and troubleshooting process in networks,” Aaron said. “They say ‘video killed the radio star,’ and now artificial intelligence, natural language processing, and natural language understanding (NLU) are going to kill the dashboard star.

“Looking ahead, the days of hunting and pecking or looking at charts will go by the wayside, because you can now type in a question and get an answer or have issues flagged for you and in some cases, actually fixed on their own — known as self-driving.

“You’re going to see a trend around AI-driven assistants replacing dashboards and changing the way we troubleshoot, essentially eliminating the ‘swivel chair’ interface.”

Learn about networking trends: Latest Trends & Developments in Networking

6. Data fabrics aiding the management of unstructured data

Data fabrics intend to connect and eliminate silos across different enterprise data storage setups. 

In 2022, experts expect that data fabrics will become a planned, fleshed-out initiative for several companies, especially as their big data management needs grow in size and complexity.

Krishna Subramanian, president, co-founder, and COO of Komprise, an unstructured data management-as-a-service (DMaaS) company, believes that data fabrics will be solidified as more companies need a better solution for managing unstructured data.

“Data fabric is still a vision,” Subramanian said. “It recognizes that your data is living in a lot of places, and a fabric can bridge the silos and deliver greater portability, visibility, and governance. 

“Data fabric research has typically focused on semi-structured and structured data. But 90% of the world’s data now is unstructured — think videos, X-rays, genomics files, log files, sensor data — and this data has no defined schema. 

“Data lakes and data analytics applications cannot readily access this dark data locked in files. So data fabric technologies need to bridge the unstructured data storage, file storage and object storage, and data analytics platforms — data lakes, ML and natural language processors, image analytics, etc. 

“Analyzing unstructured data is becoming more important as machine learning relies on unstructured data. Data fabric technologies need to be open, standards-based, and look across environments. 

“In 2022, the data fabric should move from being a vision to a set of architectural principles of data management. Technology vendors need to incorporate unstructured data into their data fabric architectures, given its rising importance and sheer magnitude.”

Learn more: What is a Data Fabric?

7. Tech workers demanding new benefits

The job market is a job seeker’s market, where the demand for new staff makes it possible for candidates to ask for higher salaries and better benefits. 

For technology workers in particular, experts are predicting that organizations will not only need to offer higher salaries in 2022, but also benefits that support their professional development and personal health.

Dice, a top technology career marketplace and research company, recently released “Tech Hiring Trends for 2022” with this explanation of what technologists will expect from job offers in the next year.

“But compensation isn’t all technologists will be asking for. In the 2021 ‘Dice Tech Salary Report,’ released earlier this year, we reported on the top benefits technologists currently have and the benefits they want. As to be expected, traditional benefits, such as health insurance, paid vacation days and 401(k) matching/pension topped the list, but there were some significant gaps midway down the list in what technologists desire and what they are receiving. 

“There was a 23% gap for training and education and a 17% gap for stock programs, hinting at where employers could differentiate their offerings to attract and retain tech talent. There was also a 15% gap in flexible schedule options, which is another lesson learned in 2021 that we discuss in the ‘Flexibility in Work Structure’ section.

“We believe these are the gaps that industrious employers, and especially those who may not have the resources of larger competitors, can look to fill through new programs or adjustments to current initiatives, giving them an advantage in conversations with technologist talent.”

Learn about data science career trends: Data Science Job Market: Build a Career in Data Science

8. Shifting cloud security landscape

The cloud computing industry continues to grow into new sectors and lines of business, and at the same time, cloud computing continues to shift its identity to meet new corporate challenges and priorities.

Vishwas Manral, chief architect of cloud at McAfee Enterprise and co-chair of the Cloud Security Alliance, thinks that 2022 will likely bring change to the cloud security vendor landscape, specifically through consolidation.

“There are currently way too many cloud security tools on the market and because of this, we are now seeing a trend towards consolidation,” Manral said.

“Because of this, there is now a large number of mergers and acquisitions happening in the cloud security market with even more consolidation on the horizon.”

Learn about cloud security trends: Top Cloud Security Trends

9. Localization meets globalization in data compliance

New global data regulations and deadlines for compliance are already planned for the next few years and more continue to join the list. 

Many companies have traditionally focused on their own industries’ regulations, but as global companies continue to move to new markets with stringent policies, localized data compliance and management will be even more necessary in 2022.

Sovan Bin, CEO of Odaseva, a data management and compliance solution designed for Salesforce, said more global regulations will require action by companies. 

“Privacy regulation will continue to go global while requiring increasing localized implementation and storage,” Bin said. 

“2021 saw the China Personal Information Protection Law (PIPL) passed at astonishing speed, cementing this trend. The extent of the requirements will become clearer as implementing regulations are introduced in 2022.”

Read next: Top Data Management Platforms and Software

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