Analytics trends report 2017
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The 2017 analytics trends report highlights the evolution of big data analytics, emphasizing the growth of cloud-based services, advanced visualization applications, and machine learning integration into business processes. Key trends include modern data governance practices, increased adoption of third-party data sets, and the emergence of 'citizen integrators' who simplify data integration for self-service reporting. The report suggests significant opportunities in sales and marketing analytics, driven by regulatory changes and technology innovations.
Analytics trends report 2017
- 1. Analytics Trends Report Prepared 2017 Robert Sibo Practice Director Slalom Consulting Silicon Valley
- 3. uses truckspulling shippingcontainers Toingestit all, firmsare speedilybuildingdata refineries The cloud big data analytics arena is still evolving – far from a mature end-state with plenty of opportunities for improvement though stacked with great new capabilities
- 4. At the end of 2016 we polled our analytics leaders and vendor partners to understand where they’re seeing investments being made Partner/Market Risk Analytics Master Data Management (still…) People Analytics (Qlty of Hire, Diversity, Retention) Analytics-driven Business Tools Integrated Marketing Analytics / Automation Data Services / Open Data Commercial Adoption Machine Learning (Python, TensorFlow) Modern Data Governance (Alation, Colibra) Advanced Visualization & D3 Tools Data Wrangling Customer Personalization / ML Driven Customization Modern Data Arch. (Spanner, Time Series DB, NoSQL) Cloud BI Platforms (AWS, Google, Azure)Cloud BI Platforms (AWS, Google, Azure) Modern Data Arch. (Spanner, Time Series DB, NoSQL) Customer Personalization / ML Driven Customization Data Wrangling Advanced Visualization & D3 Tools Modern Data Governance (Alation, Colibra) Machine Learning (Python, TensorFlow) Data Services / Open Data Commercial Adoption Integrated Marketing Analytics / Automation Analytics-driven Business Tools People Analytics (Qlty of Hire, Diversity, Retention) Master Data Management (still…) Partner/Market Risk Analytics
- 6. Our project observations and the general industry points towards the following trends we’ll see emerge and grow in 2017+ Advanced visualization applications “moving traditional BI to modern BI” ‘Little AI’ works its way into Business Applications Modern Data Architecture (MDA) & the Cloud Modern data governance & metadata mastery 3rd party commercial & open data sets ”Citizen Integrators” enabled by IT
- 7. Advanced Visualization Business Applications “Moving Traditional BI to Modern BI” plus a push to embed visualizations directly into business applications is driving custom development and innovation in reporting platforms. • Visualization tools like Tableau will continue to spread across the business moving certain use cases off of “traditional BI” • More advanced use cases are including custom web development to frame visualizations along with integrated business applications and ML driven advisory services like NLP and recommendation engine • Collaboration and interaction is a must and many tools are moving quickly to allow this natively in their tools (e.g. Domo) ‘Little AI’ works its way into business applications Commercially available tools with built in machine learning capabilities will enable product managers to embed micro customization or smart workflows processing in nearly all industries. • Little AI is used to personalize customer and employee experience and provide smarter workflows for everything ranging from CRM to online grocery shopping to meeting room booking chatbots • Machine learning techniques are leveraged in many customer/partner facing tools with ease thanks to tools like Alteryx, Google Cloud, PowerBI making it available without the PhD studies Software company, Logi Analytics, polled 500 users in 2016 and found that 60% of end users leverage embedded analytics on a regular basis. Compare that to only 21% user adoption of standalone self-service analytics 40% Increase in regular usage from embedding analytics HubSpot Global AI Survey, Q4 2016. n=1426 consumers 74% people used voice search in past month 47% would buy from a chatbot
- 8. Modern Data Architecture & the Cloud Cloud platforms provide big data and much more with little of the maintenance headaches. Quick to explore and quick to add on features coming from innovators like Google. • Quick expansion into the cloud for everything from infrastructure to analytics services (e.g. ML API) allows companies to leap frog without large investments internally on skills and costly implementations • Google Spanner – Global ACID compliant database platform on the cloud provides a unique and powerful option for global low-latency use cases • Cloud providers move towards value-add services to increase solution stickiness including ML APIs and data ingestion tools • SaaS offerings provide way to bypass upgrade dilemmas by always keeping your services up to date in exchange for a subscription fee Modern Data Governance & Metadata Mastery Moving beyond power point processes and definitions modern tools automatically rationalize data sources, look at usage patterns and map data lineage from A to Z. • Master Data Management, Data Governance and related topics haven’t gone away but now tools are popping up (e.g. Alation and Colibra) that facilitate workflows, ownership and monitoring of these capabilities • Alation and others allow BI teams to monitor and automatically catalog what reports, data sets and users are out there including SQL queries • Real data lineage and impact analysis is coming to fruition with cataloging tools from Informatica and Alation fulfilling a very old promise from DG tools 30-50% YoY growth for Cloud providers like Azure, AWS and GCP In 2014, cloud data warehousing services led the information management category in increased adoption rate, jumping from 24% to 34% according to surveys by Information Week 43% Organizations looking to deploy cloud based solutions for Big Data Analytics in 2016 * 61% Organizations reported correlating data from difference silos as one of the key challenges for Big data * * WebProNews Survey
- 9. 3rd Party Commercial & Open Data Sets Every company is a data business and the access to it provides competitive advantages so it’s no surprise data brokers are providing data to companies of all sorts who are mature enough to leverage it. • Anonymized 3rd party data sets used to provide benchmarks/baseline context for internal reporting and even wrapped and delivered to customers as enhanced services • Integrated commercial data sets and Open Data sets make their way into analytics tools like Alteryx, Google Cloud Platform to make it easy to include without negotiating data licenses or vetting for trustworthiness. • More and more companies are providing their data to other companies as they see the value of it outside their own business ”Citizen Integrators” enabled by IT Business users need to build their own integration to gather and prepare data for their self service reporting needs. Library and subscription hubs will provide democratization of internal and external data for them. • Data libraries (e.g. Paxata, Alteryx Gallery, Informatica Data Hub) provide users portal for ad-hoc and subscribed access to their company’s data assets - providing the costly data integration services behind the scenes • Alteryx and others continue to spread across business units to fill gap of data prep tools not filled by traditional IT run integration capabilities • Mature ETL tools and reporting platforms are expanding quickly into this area though By 2018 Gartner predicts 50% of integration will be implemented by Citizen Integrators in the business 50% of integration will come from Citizen Integrators Average hours spent by business user spends collecting data. Data scientists spend 60% of their time on cleaning and organizing data. Collecting data sets comes second at 19% of their time Hours Per Week3.6 The average marketing team is spending about 16 hours per week on routine tasks. About 3.55 hours are spent simply collecting and organizing data.
- 10. Our project observations and the general industry points towards the following trends we’ll see emerge and grow in 2017+ Advanced visualization business applications “moving traditional BI to modern BI” • Visualization tools like Tableau will continue to spread across the business moving certain use cases off of “traditional BI” • More advanced use cases are including custom web development to frame visualizations along with integrated business applications and ML driven advisory services like NLP and recommendation engine • Collaboration and interaction is a must and many tools are moving quickly to allow this natively in their tools (e.g. Domo) ‘Little AI’ works its way into business applications • Little AI is used to personalize customer and employee experience and provide smarter workflows for everything ranging from CRM to online grocery shopping to meeting room booking chatbots • Machine learning techniques are leveraged in many customer/partner facing tools with ease thanks to tools like Alteryx, Google Cloud, PowerBI making it available without the PhD studies Modern Data Architecture (MDA) & the Cloud • Quick expansion into the cloud for everything from infrastructure to analytics services (e.g. ML API) allows companies to leap frog without large investments internally on skills and costly implementations • Google Spanner – Global ACID compliant database platform on the cloud provides a unique and powerful option for global low-latency use cases • Cloud providers move towards value-add services to increase solution stickiness including ML APIs and data ingestion tools • SaaS offerings provide way to bypass upgrade dilemmas by always keeping your services up to date in exchange for a subscription fee Modern data governance & metadata mastery • Master Data Management, Data Governance and related topics haven’t gone away but now tools are popping up (e.g. Alation and Colibra) that facilitate workflows, ownership and monitoring of these capabilities • Alation and others allow BI teams to monitor and automatically catalog what reports, data sets and users are out there including SQL queries • Real data lineage and impact analysis is coming to fruition with cataloging tools from Informatica and Alation fulfilling a very old promise from DG tools 3rd party commercial & open data sets • Anonymized 3rd party data sets used to provide benchmarks/baseline context for internal reporting and even wrapped and delivered to customers as enhanced services • Integrated commercial data sets and Open Data sets make their way into analytics tools like Alteryx, Google Cloud Platform to make it easy to include without negotiating data licenses or vetting for trustworthiness. • More and more companies are providing their data to other companies as they see the value of it outside their own business ”Citizen Integrators” enabled by IT • Data libraries (e.g. Paxata, Alteryx Gallery, Informatica Data Hub) provide users portal for ad-hoc and subscribed access to their company’s data assets - providing the costly data integration services behind the scenes • Alteryx and others continue to spread across business units to fill gap of data prep tools not filled by traditional IT run integration capabilities • Mature ETL tools and reporting platforms are expanding quickly into this area though
- 11. Putting on a business lens we see big opportunities in partner and customer facing areas especially Sales & Marketing Analytics • Supplier Responsibility rules driven by social and regulatory pressures continues to make news for companies like Apple and requires extensive transparency reporting and full supply chain data management • Fines for trading with black listed companies can be huge financially but also take a toll on the brand Supply Chain Analytics • Business strategy aligned metrics and risk tolerance levels by key risks categories (Capital, Credit, Market, Operation, Liquidity, Reputational, Strategic) • Regulations continue to drive innovation. The EU General Data Protection Regulation's (GDPR) 72-hour data breach notification requirement is set to take effect in May 2018. • Fraud protection pushes for real-time alerting and data management around customer and partner data where fines can be dramatic (e.g. AML / KYC and channel partner management) Finance Analytics • Tools will make it easier to combine click stream and other customer channel data with revenue, workforce and sales data for richer insights • Channel partner analytics allows detailed performance and fraud monitoring and even recommend remediation such as training and certification programs to improve channel sales • CEOs are looking to reduce cost and increase revenue per FTE which requires truly treating employees as assets by standing up a People Analytics function within the organization • Quality of Hire leveraging mixture of personality, skills and performance modeling to optimize successful placement • Employee Journey is common place borrowing successes seen in marketing by mapping out the makes/breaks of sales journeys • Tools like Visier and custom built analytic solutions are popping up all over to address emerging demands: • For example, $m are lost due to improper or poorly timed On/Off Boarding that could be saved People / HR Analytics
- 12. Slalom’s State of Analytics Medium Forum: https://medium.com/state-of-analytics CIO.com’s Predictions: http://www.cio.com/article/3166060/analytics/15-data-and-analytics-trends-that-will-dominate-2017.html Supplier Responsibility @ Apple: https://www.macrumors.com/2017/03/27/apples-2017-supplier-responsibility-report/ People Analytics Pulse Survey by PWC: http://www.pwc.com/us/en/hr-management/publications/trends-workforce-people-analytics.html EU GDPR News: https://www.bna.com/eu-72hour-breach-n73014447213/ HBR – ‘7 Ways to Introduce AI into Your Organization’: https://hbr.org/2016/10/7-ways-to-introduce-ai-into-your-organization Citizen Integrator - Gartner “Predicts 2015: Digital Business and Internet of Things Add Formidable Integration Challenges”, Benoit J. Lheureux et al., November 2014, Foundational May 2016 HubSpot Global AI Survey, Q4 2016: https://research.hubspot.com/reports/artificial-intelligence-is-here Big Data Trends in Finance from MapR: https://mapr.com/blog/top-10-big-data-trends-2017-financial-services/ Tableau BI Trends 2017: https://www.tableau.com/learn/whitepapers/top-10-business-intelligence-trends-2017, https://www.tableau.com/about/blog/2016/12/whats-big-big-data-10-trends-2017-63627 Datapine Software Trends for 2017: http://www.datapine.com/blog/business-intelligence-trends-2017/# Forrester Report: https://www.forrester.com/report/Its+Time+To+Upgrade+Business+Intelligence+To+Systems+Of+Insight/-/E-RES122481 Nucleus Research / Logi Analytics ‘State of Embedded Analytics’ Report: http://go.logianalytics.com/rs/793-ECD-841/images/2017%20State%20of%20Embedded%20Analytics_Logi_final.pdf Gil Press @ Forbes: https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/#7f2e614c6f63 DEJ’s summary and analysis of 19 vendor briefings conducted around the 2016 Strata Conference, NYC: https://www.slideshare.net/dej_io/2016-strata-conference-new-york-vendor-briefings?qid=adf2cc4e-c513- 4497-a25f-fb6c542c2edc&v=&b=&from_search=6 WebProNews Survey on Marketing Tasks: http://www.webpronews.com/survey-looks-at-time-spent-by-marketers-on-email-data-collection-2016-01/ Reading Material