The document discusses six emerging trends in business analytics:
1. Humans and machines will increasingly work together in complementary roles, with machines handling tasks like data processing and humans focusing on creativity, empathy, and oversight of machine performance.
2. Analytics capabilities are expanding across entire organizations to create "insight-driven organizations" and scale initiatives from targeted areas to the enterprise level.
3. Cybersecurity is becoming more important as threats evolve, requiring proactive approaches like predictive modeling rather than just reactive defenses.
4. The Internet of Things is expanding to include people and generating new business models by aggregating and analyzing behavioral data.
5. Companies are addressing talent shortages by cultivating external talent providers and collaboration with
Guide to Data Analytics: The Trend That's Reshaping the Insurance IndustryApplied Systems
Information you need is in your management system –- you just have to understand how to use it. Read this guide to learn what data analytics is, how it's impacting the insurance industry, why it's important for independent agencies and brokerages, and how to create your own data analytics strategy.
As 2017 begins, we are seeing big data and data science communities engage with new tools that specifically cater to data scientists and data engineers who aren’t necessarily experts in these techniques. Given rapid technological advances, the question for companies now is how to integrate new data science capabilities into their operations and strategies—and position themselves in a world where analytics can upend entire industries. Leading companies are using their data science capabilities not only to improve their core operations but also to launch entirely new business models.
An enormous amount of valuable information is out there- waiting to be transformed into mission driving insights. But to excavate those insights, we must first assemble the right data science team.
Big Data : From HindSight to Insight to ForesightSunil Ranka
When it comes to Analytics and Reporting , There is a fine line between HindSight to Insight to Foresight . With the evolution of BigData technology, there is a need in deriving value out of the larger datasets, not available in the past. Even before we can start using the new shiny technologies, there is a need of understanding what is categorized as reporting or business intelligence or Big Data and Analytics. Based on my experience, people struggle to distinguish between reporting, Analytics, and Business Intelligence.
Guide to Data Analytics: The Trend That's Reshaping the Insurance IndustryApplied Systems
Information you need is in your management system –- you just have to understand how to use it. Read this guide to learn what data analytics is, how it's impacting the insurance industry, why it's important for independent agencies and brokerages, and how to create your own data analytics strategy.
As 2017 begins, we are seeing big data and data science communities engage with new tools that specifically cater to data scientists and data engineers who aren’t necessarily experts in these techniques. Given rapid technological advances, the question for companies now is how to integrate new data science capabilities into their operations and strategies—and position themselves in a world where analytics can upend entire industries. Leading companies are using their data science capabilities not only to improve their core operations but also to launch entirely new business models.
An enormous amount of valuable information is out there- waiting to be transformed into mission driving insights. But to excavate those insights, we must first assemble the right data science team.
Big Data : From HindSight to Insight to ForesightSunil Ranka
When it comes to Analytics and Reporting , There is a fine line between HindSight to Insight to Foresight . With the evolution of BigData technology, there is a need in deriving value out of the larger datasets, not available in the past. Even before we can start using the new shiny technologies, there is a need of understanding what is categorized as reporting or business intelligence or Big Data and Analytics. Based on my experience, people struggle to distinguish between reporting, Analytics, and Business Intelligence.
Why Everything You Know About bigdata Is A LieSunil Ranka
As a big data technologist, you can bet that you have heard it all: every crazy claim, myth, and outright lie about what big data is and what it isn't that you can imagine, and probably a few that you can't.If your company has a big data initiative or is considering one, you should be aware of these false statements and the reasons why they are wrong.
This white paper: Analyzes the big data revolution and the potential it offers organizations. Explores the critical talent needs and emerging talent gaps related to big data. Offers examples of organizations that are meeting this challenge head on. Recommends four steps HR and talent management professionals can take to bridge the talent gap.
The presentation is a introduction to Big Data and analytics, how to go about enabling big data and analytics in our company, what are the main differences between big data analytics vs. traditional analytics and how to get started.
This material was used at the SAS Big Data Analytics event held in Helsinki on 19th of April 2011.
The slides are copyright of Accenture.
How to use your data science team: Becoming a data-driven organizationYael Garten
Talk given at Strata Hadoop World conference March 2016.
http://conferences.oreilly.com/strata/hadoop-big-data-ca/public/schedule/detail/48305
In this talk we review the culture, process and tools needed for a data driven organization. We review an example of how companies like LinkedIn use data to make business decisions, and then walk through the culture, process, and tools needed to foster this. We review the spectrum of data science used within an organization and explore organizational needs, such as the democratization of data via self-serve data platforms for experimentation, monitoring, and data exploration, as well as the challenges that come with such systems. Participants leave this session with the ability to identify opportunities for data scientists to contribute within their organization and with an understanding of what investments are needed to drive transformation into a data-driven organization.
“People analytics” is a frequently used buzzword. But questions remain as to why this is becoming such a prominent challenge for HR. What are leading organizations doing to develop their understanding of how data analytics can drive better people decisions? In this session, learn what you can start doing tomorrow to accelerate and mobilize your people analytics efforts.
Learning Objectives
• Learn the research and trends in data & analytics.
• Learn what is driving the people analytics movement.
• Learn the barriers to entry for companies.
• Learn how to mobilize your efforts in building out your people & analytics capabilities.
Speaker: Diego Gomez, Vice President of Human Capital Management Transformation, Oracle
Met 80 procent van de klantdata wordt dit jaar niets gedaan. Hoeveel geld laat uw organisatie daardoor liggen? Data is geld waard. Bedrijven die vooruitdenken, managen hun data zo dat ze er winst uit halen. En dat geeft ze een flinke voorsprong.
What every product manager needs to know about data science (ProductCamp Bost...ProductCamp Boston
Product management and data science work in close partnership at many of the highest performing organizations, which use analytics to develop better products, drive customer acquisition and retention, and create additional revenue streams. Not all organizations have the resources or desire to build an internal data science competency, but all can benefit from some degree of analytical orientation. When armed with basic quantitative literacy, product managers are often among the best positioned individuals in their organizations to recognize and build strong business cases around data related opportunities worth pursuing.
This presentation covers, through practical case studies, the information that all product managers should know about data science. Attendees will leave better able to recognize data related opportunities, understand the potential benefits and risks, build business cases for analytics, and learn more.
About Trevor Bass
Trevor Bass is a data scientist with a decade of experience building highly successful and innovative products and teams. He runs Bitten Labs, a data science management consultancy, education provider, and innovation lab. Prior to Bitten Labs, Trevor founded and built the data science function at payment processor Litle & Co (acquired by Vantiv), which performed product R&D, drove customer acquisition, retention, and upselling, provided quantitative consulting throughout the company and for its end customers, and established clear industry thought leadership. Trevor holds a Master's degree from Rutgers University and a Bachelor's degree magna cum laude from Harvard University, both in mathematics.
This study evaluates the scenario of analytics and data science hirings across various industries such as retail, telecom, e-commerce etc, across cities, requirements in terms of experience & education, hiring trends and much more.
The 10 Most Admired Analytics Companies to Watch in 2018Merry D'souza
We introduce “The 10 Most Admired Analytics Companies to Watch in 2018”, in order to assist businesses to choose their right analytics companies. Assessing the scenario in versatile perceptions, our magazine has brought light onto the companies, who have flaunted excellence in providing technologically advanced analytics solutions. This list showcases the analytics companies which are creating a better ‘Analytics’ world.
Unlocking Value of Data in a Digital AgeRuud Brink
InfoGraphic about Intelligence Hubs as accelerator of the Digital organisation. Five steps how you could think big, and act small to unlock value of Data in your organisation. Contact me for the office A0 poster.
Why Everything You Know About bigdata Is A LieSunil Ranka
As a big data technologist, you can bet that you have heard it all: every crazy claim, myth, and outright lie about what big data is and what it isn't that you can imagine, and probably a few that you can't.If your company has a big data initiative or is considering one, you should be aware of these false statements and the reasons why they are wrong.
This white paper: Analyzes the big data revolution and the potential it offers organizations. Explores the critical talent needs and emerging talent gaps related to big data. Offers examples of organizations that are meeting this challenge head on. Recommends four steps HR and talent management professionals can take to bridge the talent gap.
The presentation is a introduction to Big Data and analytics, how to go about enabling big data and analytics in our company, what are the main differences between big data analytics vs. traditional analytics and how to get started.
This material was used at the SAS Big Data Analytics event held in Helsinki on 19th of April 2011.
The slides are copyright of Accenture.
How to use your data science team: Becoming a data-driven organizationYael Garten
Talk given at Strata Hadoop World conference March 2016.
http://conferences.oreilly.com/strata/hadoop-big-data-ca/public/schedule/detail/48305
In this talk we review the culture, process and tools needed for a data driven organization. We review an example of how companies like LinkedIn use data to make business decisions, and then walk through the culture, process, and tools needed to foster this. We review the spectrum of data science used within an organization and explore organizational needs, such as the democratization of data via self-serve data platforms for experimentation, monitoring, and data exploration, as well as the challenges that come with such systems. Participants leave this session with the ability to identify opportunities for data scientists to contribute within their organization and with an understanding of what investments are needed to drive transformation into a data-driven organization.
“People analytics” is a frequently used buzzword. But questions remain as to why this is becoming such a prominent challenge for HR. What are leading organizations doing to develop their understanding of how data analytics can drive better people decisions? In this session, learn what you can start doing tomorrow to accelerate and mobilize your people analytics efforts.
Learning Objectives
• Learn the research and trends in data & analytics.
• Learn what is driving the people analytics movement.
• Learn the barriers to entry for companies.
• Learn how to mobilize your efforts in building out your people & analytics capabilities.
Speaker: Diego Gomez, Vice President of Human Capital Management Transformation, Oracle
Met 80 procent van de klantdata wordt dit jaar niets gedaan. Hoeveel geld laat uw organisatie daardoor liggen? Data is geld waard. Bedrijven die vooruitdenken, managen hun data zo dat ze er winst uit halen. En dat geeft ze een flinke voorsprong.
What every product manager needs to know about data science (ProductCamp Bost...ProductCamp Boston
Product management and data science work in close partnership at many of the highest performing organizations, which use analytics to develop better products, drive customer acquisition and retention, and create additional revenue streams. Not all organizations have the resources or desire to build an internal data science competency, but all can benefit from some degree of analytical orientation. When armed with basic quantitative literacy, product managers are often among the best positioned individuals in their organizations to recognize and build strong business cases around data related opportunities worth pursuing.
This presentation covers, through practical case studies, the information that all product managers should know about data science. Attendees will leave better able to recognize data related opportunities, understand the potential benefits and risks, build business cases for analytics, and learn more.
About Trevor Bass
Trevor Bass is a data scientist with a decade of experience building highly successful and innovative products and teams. He runs Bitten Labs, a data science management consultancy, education provider, and innovation lab. Prior to Bitten Labs, Trevor founded and built the data science function at payment processor Litle & Co (acquired by Vantiv), which performed product R&D, drove customer acquisition, retention, and upselling, provided quantitative consulting throughout the company and for its end customers, and established clear industry thought leadership. Trevor holds a Master's degree from Rutgers University and a Bachelor's degree magna cum laude from Harvard University, both in mathematics.
This study evaluates the scenario of analytics and data science hirings across various industries such as retail, telecom, e-commerce etc, across cities, requirements in terms of experience & education, hiring trends and much more.
The 10 Most Admired Analytics Companies to Watch in 2018Merry D'souza
We introduce “The 10 Most Admired Analytics Companies to Watch in 2018”, in order to assist businesses to choose their right analytics companies. Assessing the scenario in versatile perceptions, our magazine has brought light onto the companies, who have flaunted excellence in providing technologically advanced analytics solutions. This list showcases the analytics companies which are creating a better ‘Analytics’ world.
Unlocking Value of Data in a Digital AgeRuud Brink
InfoGraphic about Intelligence Hubs as accelerator of the Digital organisation. Five steps how you could think big, and act small to unlock value of Data in your organisation. Contact me for the office A0 poster.
Evolution of Data Analytics: the past, the present and the futureVarun Nemmani
This paper delves into the topic of advanced analytics, the current industry demands to utilize and analyze huge/diverse amounts of data, how big data analytics is becoming a part of the decision making process and to anticipate trends. This paper takes the reader from Analytics era 1.0 to the current Analytics era 3.0; shows the future projections of big data analytics and also the current leaders of the Big Data Analytics market.
Big Data Courses In Mumbai at Asterix Solution is designed to scale up from single servers to thousands of machines, each offering local computation and storage. With the rate at which memory cost decreased the processing speed of data never increased and hence loading the large set of data is still a big headache and here comes Hadoop as the solution for it.
http://www.asterixsolution.com/big-data-hadoop-training-in-mumbai.html
10 Enterprise Analytics Trends to Watch in 2019 MicroStrategy
View insights from Forrester analyst Mike Gualtieri, Constellation Research’s Ray Wang and Doug Henschen, Ventana Research’s Mark Smith and David Menninger, IDC’s Chandana Gopal, Marcus Borba, Ronald van Loon and other top analytics and business intelligence thought leaders.
The ability to continuously innovate is crucial for business growth – and often necessary for survival. Leaders in an uncertain and fast-paced global business regularly seek innovation to revitalise rigid business models and processes. However, they are aware that ‘innovation is hard’ and fraught with uncertainty. I contend that Big Data Analytics – in addition to its many other business benefits – can guide the innovation process to make it more efficient, effective and predictable.
Big Data Analytics promotes the application of a data-driven mindset that ‘listens to the data’ for new insights and disrupts entrenched thinking that hinders innovation. It applies what-if analysis to assess impact of new ideas on key business metrics and uses evidence-based business performance analysis to track the impact of innovation. Integrating Big Data Analytics into the business planning and operational processes provides valuable feedback loops and enables an adaptive innovation process.
In short, Big Data Analytics can spark innovation, guide its refinement and adoption processes and sustain its ongoing implementation.
Presentation about the state of AI, policy-relevant AI research and evidence gaps that can be addressed with new data, methods and modelling approaches.
Big Data Update - MTI Future Tense 2014Hawyee Auyong
The Futures Group first wrote about the emerging phenomenon of Big Data in 2010 as it was about to enter the mainstream. It was envisaged that Big Data would create a demand for new skills (Google has identified statisticians as the “sexy job of the decade”) and generate new industries. This report updates on the industry value chain and business models for the data analytics industry, latest developments as well as the opportunities for Singapore.
Operationalizing the Buzz: Big Data 2013VMware Tanzu
The 2013 EMA/9sight Big Data research makes a clear case for the maturation of Big Data as a critical approach for innovative companies. This year’s survey went beyond simple questions of strategy, adoption and use to explore why and how companies are utilizing Big Data. This year’s findings show an increased level of Big Data sophistication between 2012 and 2013 respondents. An improved understanding of the “domains of data” drives this increased sophistication and maturity. Highly developed use of
Process-mediated, Machine-generated and Human-sourced information is prevalent throughout this year’s study.
10 Enterprise Analytics Trends to Watch in 2020MicroStrategy
As businesses face a 2020 reality check and use this year to hone their strategy for the next decade, MicroStrategy has compiled insights on the top enterprise analytics trends to watch from leading BI, analytics and digital transformation influencers including analysts from Forrester, IDC, Constellation Research, Ventana Research and more.
From artificial intelligence and mobile intelligence, to the explosion of data and data sources, to some very human factors, we hope you’ll find this gathering of insights (plus the patterns and themes that have emerged here) a valuable resource for taking action now, but also looking and planning ahead to become an Intelligent Enterprise.
Similar to Analytics trends 2016 the next evolution (20)
eyond digitalizing money, payments, economics, and finance, blockchains are a singularity-class technology that enables the secure, trackable, automated coordination of very large-scale projects, fleets, and swarms
The implications could be an orderly transition to the automation economy and trust-rich human-machine collaboration in the digital smartnetwork societies of the future
Social media represents the pulse of the planet, it can shape our ideas and identify new products and markets, help us identify opportunities for our businesses. The trick is how to tap into that channel. IBM Watson Analytics for Social Media is a cloud-based smart data discovery service which puts advanced analytics, without complexity, right at your fingertips! See how Highlands and Islands can get answers and new insights to inform business decisions.
What's new in ibm notes and ibm domino v1Yann Lecourt
Introduction
IBM Notes Domino - Year in Review
IBM Notes Domino - Roadmap and Futures
Domino Security: Present and Future
SmartCloud Notes/Verse – Year in Review
SmartCloud Notes/Verse – Roadmap and Futures
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Building RAG with self-deployed Milvus vector database and Snowpark Container...Zilliz
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
2. As the discipline of business analytics matures,
it’s clear that some trends aren’t going away.
Instead, they are evolving at such a rapid pace
that they demand a fresh look every year.
This year, we’re taking stock of a mix of both new
and familiar trends that are shaping an “everywhere
analytics” world—where analytics, data, and reasoning
are embedded into the decision-making process,
every day, everywhere in the organization.
Analytics Trends 2016 | 2
4. The man-machine
dichotomy blurs
As cognitive capabilities advance, where do humans fit
into the picture? Fear not—there’s still a place for us.
In the near future, human insights and instincts will
complement machine-driven insights. What will this
more collaborative future look like?
Analytics Trends 2016 | 4
5. Humans and machines will find new
ways to complement one another
• Humans will build and implement
cognitive technologies
• Humans must ensure machine performance
and fit with work processes
• Humans will perform roles that computers
can’t – such as those involving creativity,
caring, or empathy
The way forward
• Examine knowledge-intensive processes
to determine which tasks are performed
by machines, and which by humans
• Plan for some degree of retraining
$1 billion
in venture capital funding
for cognitive technologies
in 2014 and 2015
Market revenue for
cognitive expected to exceed
$60 billionby 2025
The cognitive age is here
The man-machine dichotomy blurs
Analytics Trends 2016 | 5
Source: International Data Corporation
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
7. Analytics expands
across the enterprise
Not long ago, it was enough to simply get targeted
analytics capabilities put in place. Today, a new goal is
emerging: The insight-driven organization. That will
require scaling small, current analytics initiatives to the
enterprise level. From “analytics transformation” to
“industrialized analytics,” get ready.
Analytics Trends 2016 | 7
8. A new goal emerges: The insight-driven
organization (IDO)
• Yesterday: Implement or improve targeted
analytics capabilities in a few key areas
• Tomorrow: Tightly knitted combo of strategy,
people, processes, data, and technology that
delivers insights every day, everywhere in the organization
Shaping an IDO future with today’s decisions
• Some leaders are already discussing “analytics
transformation” and “industrialized analytics”
• Decisions on issues such as data warehouses
and big data must be made in the context
of an IDO future
The way forward
• Take existing analytics initiatives and
scale them to the enterprise level
• Goal: Grow and connect analytics
capabilities across the enterprise
Analytics expands across the enterprise
Analytics Trends 2016 | 8www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
10. Cybersecurity:
A good defense
isn’t enough
Last year’s supertrend is still front and center—
growing in importance as more organizations
experience the losses in value and reputation that can
result from security lapses. Some organizations are
taking the offensive when it comes to cybersecurity—
which requires new thinking and approaches.
Analytics Trends 2016 | 10
11. Persistent and evolving
• Product design and other IP are vulnerable to
theft and sabotage—protecting data is only part
of the challenge
• Cybercriminals are becoming more skilled
Scanning the current cybersecurity landscape
• Leaders are taking steps to become proactive,
not reactive
• Big spending is expected to continue
• Rise in automated scanning of Internet chatter,
analysis of past hacks to create predictive models
that anticipate the next threats, and more
The way forward
• Enhance collaboration between analytics
and cyber professionals
• Adopt more predictive approaches
to threat intelligence and monitoring
U.S. federal government agencies
alone will have spent more than
$14.5 billion
on IT security in 2015
The worldwide financial
services industry will have spent
$27.4 billion
on information security and
fraud prevention in 2015
Growing investments
in cybersecurity
Cybersecurity: A good defense isn’t enough
Analytics Trends 2016 | 11
Source: International Data Corporation, “Big
Data and Predictive Analytics: On the
Cybersecurity Front Line,” February 2015.
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
13. The Internet of Things
– and people, too
As the Internet of Things matures, it’s moving beyond the
interesting gadgets on which it relies to include tracking
people as “things.” And it’s spawning new business models
along the way.
Analytics Trends 2016 | 13
14. Beyond gadgetry
• New roles for people in the IoT: Connected customers
automatically transmitting data on aspects of their behavior
or preferences, workers outfitted with wearables that share
information on activities and whereabouts, and more
• This is spawning new business models and leading to
new ways to influence behaviors
A new source of innovation
• Data generated by IoT assets is being aggregated
and analyzed to create new products and services
• Big benefits to society at large are more likely as a result
− More energy- and time-efficient transportation
− More transparent, economical government services
… and much more
The way forward:
• Build on existing infrastructure: Much of what is
required to enable IoT is already in place
• Give people incentives for participating in IoT—like
health insurers offering discounts to track customer
fitness activities using wearables
The worldwide IoT market
is expected to grow from
$655.8 billion
in 2014 to
$1.7 trillion
in 2020
Too big to ignore?
The Internet of Things – and people, too
Analytics Trends 2016 | 14
Sources: International Data Corporation,
“IDC’s Worldwide Internet of Things
Taxonomy, 2015,”
“Worldwide Internet of Things Forecast,
2015-2020,” “Worldwide IoT Spending Guide
by Vertical”
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
15. The Internet of Things – and people, too
Impact
Analytics Trends 2016 | 15
16. Companies bridge
the talent gap
The business world is coming to terms with the fact
that the supply of data scientists (and others with
related skills) can’t keep up with demand. So they’re
getting creative. From new recruitment strategies to
tapping the capabilities of a broader talent ecosystem,
expect the analytics leaders of 2016 to find a way.
Analytics Trends 2016 | 16
17. A deepening shortage
• Universities can’t crank out data scientists
and others fast enough to keep up
with business demands
• Only 17% of “analytically challenged”
firms report having the talent they need
Expanding avenues for talent
• Analytics and data science programs
are on the rise in universities
• Providers of analytics talent are also on the rise— often
in highly specialized areas such as business intelligence,
predictive analytics, data science, and cognitive
technology
The way forward
• Recruitment: Collaborate more closely
with university programs on internships
and student projects
• The talent ecosystem: Cultivate ecosystems
of external providers of analytics skills
International Data Corporation
predicts a need for
181,000
people
with deep analytics skills
in the U.S. by 2018
How much talent
is enough?
Companies bridge the talent gap
Analytics Trends 2016 | 17
Source: International Data Corporation
www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
19. Business borrows
from the sciences
Scientists have been applying advanced analytics
techniques to their toughest challenges for years, in
everything from molecular biology to astrophysics.
Now, their business-world counterparts are beginning
to borrow many of those techniques for their own
purposes – jump-starting their efforts with more
sophisticated capabilities.
Analytics Trends 2016 | 19
20. Scientists were into analytics before it was cool
• The discipline of analytics isn’t new—scientists have been
advancing analytics techniques for decades
• Techniques developed for scientific purposes hold
significant potential for addressing business challenges
Cross-pollination has already begun
• Analytics developed for DNA research have
been applied to text analytics initiatives
• One prominent private company hired dozens
of scientists from a major research university
• Developments like these are in their nascent
stages now—but a burst of activity is likely
The way forward
• Hire broadly from multiple disciplines spanning
statistical, biological, and physical sciences
• Expand and clarify the career track for data
scientists
• For companies that are not high-tech: Determine whether
your organization can viably compete with start-ups and
other advanced industries for the talent and skills you need
Business borrows from the sciences
Analytics Trends 2016 | 20www.deloitte.com/us/AnalyticsTrends #AnalyticsTrends2016
22. To learn more, visit www.deloitte.com/us/AnalyticsTrends
Follow @DeloitteBA on Twitter
Share your thoughts with the hashtag #AnalyticsTrends2016
Analytics Trends 2016 | 22
23. Forrest Danson
Principal
US Leader, Deloitte Analytics
Deloitte Consulting LLP
fdanson@deloitte.com
Tom Davenport
Independent Senior Advisor
Deloitte Analytics
tdavenport@babson.edu
Jim Guszcza
Senior Manager
Chief Data Scientist
Deloitte Consulting LLP
jguszcza@deloitte.com
John Lucker
Principal
Global Advanced Analytics
Market Leader
Deloitte Consulting LLP
jlucker@deloitte.com
Jon Raphael
Partner
Audit Chief Innovation Officer
Deloitte & Touche LLP
jraphael@deloitte.com
Adnan Amjad
Partner
Cyber Risk Services
Deloitte & Touche LLP
aamjad@deloitte.com
Steven Gold
Principal
Enterprise Science Leader
Deloitte Consulting LLP
stevegold@deloitte.com
Vivek Katyal
Principal
US Risk Analytics Leader
Deloitte & Touche LLP
vkatyal@deloitte.com
Beth Mueller
Partner
US Tax Analytics Leader
Deloitte Tax LLP
bethmueller@deloitte.com
Trend Watchers
Analytics Trends 2016 | 23