In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event, the focus was largely on machine learning and artificial intelligence (AI). That theme continued this year, but my impression of the event was of a community looking to get value out of data regardless of the technology being used to manage that data. The change was subtle: The location was the same; the exhibitors were largely the same; attendance was similar this year and last. But there was no particular vendor or technology dominating the event.
Topics: Big Data, Data Science, Machine Learning, Analytics, Business Intelligence, Data Governance, Data Integration, Data Preparation, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing
From Analytics to Action Requires Collaboration
All too often, software vendors view analytics as the end rather than the beginning of a process. I’m reminded of some of the advanced math classes I’ve taken in which the teaching process focused on a few key aspects of a mathematical proof or solution, leaving the rest of the exercise to be worked out by the students. In other contexts, you may hear people say the numbers speak for themselves.
Topics: Data Science, Machine Learning, business intelligence, Analytics, Collaboration, Data Governance, Information Optimization, Digital Technology, collaboration for business
We now are well beyond the year depicted in 2001: A Space Odyssey, a cinematic perspective on the future of artificial intelligence in which HAL 9000, a computer, is able to simulate human behavior and control machines. Anyone reviewing the past two years of marketing around AI in the business technology industry can be forgiven for believing that we have arrived at the futuristic state Stanley Kubrick imagined. We have not.
Topics: Big Data, Data Science, Mobile, Customer Analytics, Customer Engagement, Customer Experience, Machine Learning, Mobile Technology, Analytics, Business Intelligence, Cloud Computing, Collaboration, Customer Service, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing, Cybersecurity, Billing and Recurring Revenue, Workforce Optimization, collaboration for business
Beyond Digital Transformation: Effective Technology Innovation in 2018
Advancing the potential of any business requires continuous improvement in the processes and technology that support it. Many companies have embraced attempts at a digital transformation, and it’s become a goal to which organizational resources and budgets have been dedicated around the globe.
Topics: Big Data, Data Science, Mobile, Sales, Customer Analytics, Customer Engagement, Customer Experience, Human Capital Management, Machine Learning, Marketing, Marketing Performance Management, Mobile Technology, Office of Finance, Wearable Computing, Analytics, Business Intelligence, Cloud Computing, Collaboration, Customer Service, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Information Optimization, Product Information Management, Digital Technology, Digital Marketing, Digital Commerce, Operations & Supply Chain, Machine Learning and Cognitive Computing, Pricing and Promotion Management, Cybersecurity, Billing and Recurring Revenue, Workforce Optimization, collaboration for business, mobile marketing
Broken Analytics and BI? Natural Language and Notifications Can Help
If we look at the focus of technology vendors for analytics and business intelligence or business applications providers deploying these capabilities in the last five years, we see that they have elevated the importance on the value of visualization and dashboards. These promotions might be understandable, but will they make business and the people using them more intelligent?
Topics: Big Data, Data Science, Mobile, Machine Learning, Analytics, Business Intelligence, Cloud Computing, Collaboration, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing
Informatica Asserts Its Commitment to the Cloud and Machine Learning
Informatica reintroduced itself to the world at its recent customer conference, Informatica World, in San Francisco. The company took advantage of the event to showcase its new branding in an effort to change the way customers think about the company. Informatica has been providing information services in the cloud for more than a decade. Even though cloud revenue comprises a minority of Informatica’s business, in absolute terms, the revenue is significant, and company executives want the public to recognize Informatica as a leader in cloud-based data management services for enterprises. Presenters also made notable product announcements, discussed below, including the application of machine learning to the data management process.
Topics: Big Data, Data Science, Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Integration, Data Preparation, Information Optimization, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
I recently attended SAS Institute’s analyst relations conference. There the company provided updates on its financial performance and its Viya platform and a glimpse into some of its future plans.
Topics: Big Data, Data Science, Mobile Technology, business intelligence, Analytics, Cloud Computing, Collaboration, Data Governance, Data Integration, Data Preparation, Internet of Things, Information Optimization, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
Cloudera provides database and enabling technology for the big data market and overall for data and information management. As my colleague David Menninger has written, the big data and information management technology markets are changing rapidly and require vendors to adapt to them. Cloudera has grown significantly over the last decade and now has approximately 1,000 customers and provides support and services in countries around the world. Its product and technology strategy is to provide a unified data management platform, Cloudera Enterprise, that can meet the data engineering and science needs for a range of analytic and operational database applications. Its primary focus is its Enterprise Data Hub, which as a data lake can handle organizations’ big data and analytical needs. As David Menninger asserts, the data lake is a safe way to invest in big data. It also helps shift the focus away from the V’s (volume, velocity and variety) of big data to the A’s, which are analytics, awareness, anticipation and action.
Topics: Big Data, Data Science, Machine Learning, business intelligence, Analytics, Cloud Computing, Data Governance, Data Integration, Data Preparation, Internet of Things, Cognitive Computing, Information Optimization, Digital Technology
Big data initially was characterized in terms of “the three V’s,” volume, velocity and variety. Nearly five years ago I wrote about the three V’s as a way to explain why new and different technologies were needed to deal with big data. Since then the industry has tackled many of the technical challenges associated with the three V’s. In 2017 I propose that we focus instead on a different letter, which includes these A’s: analytics, awareness, anticipation and action. I’ll explain why each is important at this stage of big data evolution.
Topics: Data Science, Machine Learning, Analytics, Business Intelligence, Collaboration, Data Preparation, Internet of Things, Information Optimization
The big data market continues to evolve, as I have written previously. Vendors are attempting to differentiate their offerings as they seek to encourage customers to pay for technology that they could potentially download for free.
Topics: Big Data, Analytics, Business Intelligence, Internet of Things, Information Optimization
IBM recently held its inaugural World of Watson event. Formerly known as IBM Insight, and prior to that IBM Information on Demand, the annual event, attended by 17,000 people this year, showcases IBM’s data and analytics and the broader IBM efforts in cognitive computing. The theme for the event, as you might guess, was the Watson family of cognitive computing products. I, for one, was glad to spend more time getting to know the Watson product line, and I’d like to share some of my observations from the event.
Topics: Big Data, Data Science, Machine Learning, Analytics, Cloud Computing, Data Governance, Data Integration, Internet of Things, Information Optimization, Machine Learning and Cognitive Computing
Research Finds Mobile Analytics and BI Reach Crossroads
Ventana Research has newly published its Mobile Analytics and Business Intelligence 2016 Value Index. The Value Index provides a comprehensive evaluation of vendors and their product offerings across seven categories. In performing that analysis, I realized that this software category is at a crossroads. Once an optional capability often reserved for executives, mobile analytics is becoming a requirement of business users across organizations. The blurring of lines between work and personal lives has provoked a change from single device BI to BI on multiple devices including smartphones and tablets as well as laptops and desktops. From a platform standpoint, the adoption of HTML5 is contesting the prevalence of native mobile applications.
Topics: Mobile Technology, Business Analytics, Business Intelligence, Information Optimization, Mobile BI, Analytics, Business Intelligence
Denodo Makes Data Virtualization Relevant to Big Data and Analytics
Data virtualization is not new, but it has changed over the years. The term describes a process of combining data on the fly from multiple sources rather than copying that data into a common repository such as a data warehouse or a data lake, which I have written about. There are many reasons for an organization concerned with managing its data to consider data virtualization, most stemming from the fact that the data does not have to be copied to a new location. It could, for instance, eliminate the cost of building and maintaining a copy of one of the organization’s big data sources. Recognizing these benefits, many database and data integration companies offer data virtualization products. Denodo, one of the few independent, best-of-breed vendors in this market today, brings these capabilities to big data sources and data lakes.
Topics: Big Data, Business Analytics, Business Intelligence, Information Management, Information Optimization, Data virtualization, data integration, data lake,
Next Generation of Product Information Management Empowers Digital Business
Organizations in all industries face various difficulties in managing product information. The most serious is providing complete, engaging information to consumers and customers on the internet. Newly developed products, mergers and acquisitions, changes to pricing and promotions in online commerce spur business growth, but these factors also increase the amount and complexity of product-related data and content. In addition the digital economy offers a new generation of services that are sold by subscription and packaged in various options and price points. As well, global diversification of suppliers, customers and business partners forces organizations to manage data quality and consistency in multiple locations, currencies and languages.
Topics: Big Data, Sales Performance, Supply Chain Performance, PIM, Product Information Management, Sales, Market, Customer Performance, Operational Performance, Business Analytics, Business Performance, Cloud Computing, Financial Performance, Information Management, Uncategorized, Information Optimization
It has been more than five years since James Dixon of Pentaho coined the term “data lake.” His original post suggests, “If you think of a data mart as a store of bottled water – cleansed and packaged and structured for easy consumption – the data lake is a large body of water in a more natural state.” The analogy is a simple one, but in my experience talking with many end users there is still mystery surrounding the concept. In this post I’d like to clarify what a data lake is, review the reasons an organization might consider using one and the challenges they present, and outline some developments in software tools that support data lakes.
Topics: Big Data, Predictive Analytics, Social Media, Business Analytics, Business Intelligence, Governance, Risk & Compliance (GRC), Information Management, Uncategorized, Information Optimization
New Generation of Enterprise Messaging Supports Digital Transformation
Enterprise messaging is the technology backbone of communications for applications and systems within and between organizations. Both its importance and its complexity are growing as organizations increasingly have to provide real-time responses to business customers and consumers as well as their own business professionals who support them and their internal supply chains. The variety of use cases for enterprise messaging also is growing rapidly, expanding to the Internet of Things (IoT) market of sensors and devices including wearable technology; to new generations of applications and services for consumers and customers; to cloud computing and the shift to platform or infrastructure as a service (PaaS or IaaS); and to real-time big data and analytics. All of these innovations will enable these types of transformation to digital business that is impacting organizations around the world.
Topics: Big Data, Social Media, Supply Chain Performance, Enterprise messaging, Internet of Things, IoT, mid, Mobile Technology, Customer Performance, Operational Performance, Business Performance, Cloud Computing, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Uncategorized, Information Optimization
Mastering Marketing Mayhem in a Meaningful, Meticulous Manner
I hope this title captures your attention; I’m trying to make a point about the chaos going on in managing and operating marketing. What marketing needs in 2016 is to manage and optimize its efforts in a more unified manner. This perspective kicks off a new series on the challenges for marketing to automate or execute tasks and manage toward maximum performance. We all know that the craft of marketing is in need of significant transformation, from the CMO throughout the entire marketing organization and all the way out to the experience of consumers and customers. But this may be a fanciful mission, as applications and technology does not really automate marketing let alone manage it. Most marketing automation products are specialized applications that are not used by marketing management, let alone front-line marketing managers; they are for specialized needs in demand generation or digital marketing that personalizes inbound and outbound interactions with contacts for the purpose of advancing dialogue and creating relationships. Marketing automation, like its cousin sales force automation, has been a placeholder category that describes only a narrow slice of marketing, and the term has been co-opted by the industry for its own purposes. Though some observers predict that CMOs will outspend CIOs and other leaders of the business in technology investments, I have debunked this ludicrous idea; even if it were true, that would not make marketing departments much more efficient in their management and operations. To counterbalance the silliness of the marketing automation dialogue, I plan to bring you a series on key areas for investment to start the conversation. Evaluating them should help Marketing demonstrate its commitment to promoting effectively its organization and its products and services. Here is an overview of the many issues in the landscape.
Topics: Big Data, Predictive Analytics, Social Media, Customer Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Financial Performance, Information Applications, Operational Intelligence, Uncategorized, CMO, Information Optimization, Sales Performance Management (SPM)
Qlik Makes Sense of its Analytics and Business Value
At the 2015 technology analyst summit in Austin, Texas, analytics and business intelligence software vendor Qlik discussed recent market and product developments and explained its roadmap and strategy for 2016. Discussion topics included its Qlik Analytics Platform and QlikView 12.0, Qlik Sense and Qlik DataMarket, applications built on the platform but also how it is expanding its analytics experience for business.
Topics: Big Data, Mobile Technology, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Uncategorized, Information Optimization
Digital Technology Agenda for Business in 2016
Technology innovation is accelerating faster than companies can keep up with. Many feel pressure to adopt new strategies that technology makes possible and find the resources required for necessary investments. In 2015 our research and analysis revealed many organizations upgrading key business applications to operate in the cloud and some enabling access to information for employees through mobile devices. Despite these steps, we find significant levels of digital disruption impacting every line of business. In our series of research agendas for 2016 we outline the areas of technology that organizations need to understand if they hope to optimize their business processes and empower their employees to handle tasks and make decisions effectively. Every industry, line of business and IT department will need to be aware of how new technology can provide opportunities to get ahead of, or at least keep up with, their competitors and focus on achieving the most effective outcomes.
Topics: Big Data, Predictive Analytics, Sales Performance, Supply Chain Performance, Governance, Mobile Technology, Operational Performance Management (OPM), Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Uncategorized, Workforce Performance, Business Performance Management (BPM), Financial Performance Management (FPM), Information Optimization, Sales Performance Management (SPM)
Research Agenda: Big Data and Information Optimization in 2016
The big data market continues to expand and enable new types of analyses, new business models and new revenues streams for organizations that implement these capabilities. Following our previous research into big data and information optimization, we’ll investigate the technology trends affecting both of these domains as part of our 2016 research agenda.
Topics: Big Data, Analytics, Business Analytics, Business Intelligence, Data Preparation, In-memory, Information Management, Operational Intelligence, Uncategorized, Information Optimization
Research Agenda: Using Business Analytics to Make the Most of Data in 2016
Throughout the course of our research in 2016, we’ll be exploring ways in which organizations can maximize the value of their data. Ventana Research believes that analytics is the engine and data is the fuel to power better business decisions. Several themes emerged from our benchmark research on incorporating data and analytics into organizational processes, and we will follow them in our 2016 Business Analytics Research Agenda:
Topics: Big Data, Predictive Analytics, Mobile Technology, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Information Management, Operational Intelligence, Information Optimization
Pardon the Interruption: Industry Veteran Returns to Ventana Research
Some followers of Ventana Research may recall my work here several years ago. Here and elsewhere I have spent most of my career in the data and analytics markets matching user requirements with technologies to meet those needs. I’m happy to be returning to Ventana Research to resume investigating ways in which organizations can make the most of their data to improve their business processes; for a first look, please see our 2016 research agenda on Big Data and Information Optimization. I relish the opportunity to conduct primary market research in the form of Ventana’s well-known benchmark research and to help end users and vendors apply the information collected in those studies.
Topics: Big Data, Predictive Analytics, Analytics, Business Analytics, Business Intelligence, Information Management, Internet of Things, IOT, Operational Intelligence, Unicorns, Information Optimization
IBM Redesigns Cognos to Improve User Experience and Self-Service
IBM redesigned its business intelligence platform, now called IBM Cognos Analytics. Expected to be released by the end of 2015, the new version includes features to help end users model their own data without IT assistance while maintaining the centralized governance and security that the platform already has. Our benchmark research into information optimization shows that simplifying access to information is important to virtually all (97%) participating organizations, but it also finds that only one in four (25%) are satisfied with their current software for doing that. Simplification is a major theme of the IBM Cognos redesign.
Topics: Big Data, Mobile Technology, Wearable Computing, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Uncategorized, Visualization, Cognos, Information Optimization, Risk & Compliance (GRC), Watson, cognos analytics
Stibo Systems Continues to Advance PIM for Business and IT
Stibo Systems has been providing product information management (PIM) software for decades. Its work has helped many organizations worldwide take control of their product information by developing a master definition that can be published across many channels from Web to digital to print. We recognized its work with customers Delta Faucet and Masco Corp. in our 2015 Ventana Research Leadership Award in Information Management. In 2014 Stibo Systems customer Brady Corp. won a similar award for Information Optimization. I have made it clear that in our view, when it comes to use all kinds of product content and data in business processes, product information management trumps master data management. Delivering value to business with PIM is much different than managing data infrastructure with MDM. There has been much angst in varying industry analyst views on this market segment. We analyze and rate vendors more rigorously than analyst firms that look at them only through an IT lens. Our methodology and framework put business first and IT second, and that shapes how we score vendors in PIM, MDM and other aspects of the software industry.
Topics: Master Data Management, Sales, Sales Performance, Supply Chain Performance, Customer Experience, MDM, Mobile Technology, PIM, Stibo Systems, Customer Performance, Operational Performance, Business Performance, Cloud Computing, Financial Performance, Information Management, Business Performance Management (BPM), Financial Performance Management (FPM), Information Optimization, Product Information Management
Tableau Continues Evolution of Analytics Platform
Tableau Software’s annual conference, which company spokespeople reported had more than 10,000 attendees, filled the MGM Grand in Las Vegas. Various product announcements supported the company’s strategy to deliver value to analysts and users of visualization tools. Advances include new data preparation and integration features, advanced analytics and mapping. The company also announced the release of a stand-alone mobile application called Vizable . One key message management aimed to promote is that Tableau is more than just a visualization company.
Topics: Big Data, Tableau, Mobile Technology, data viz, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Visualization, Information Optimization, Risk & Compliance (GRC)
Informatica Navigates Carefully to Broader Data Management
This has been a dramatic year for Informatica, a major provider of data integration software. In August it was acquired and taken private by Permira funds and Canada Pension Plan Investment Board for about US$5.3 billion. This change was accompanied by shifts in its management. CEO Sohaib Abbasi became chairman and now has left, and many executives were replaced while Anil Chakravathy became CEO from being the Chief Product Officer. The new owners appear to have shifted the company’s strategic priorities to emphasize profitability with reduced headcount and return on the purchase investment. Despite these changes, during the past six months Informatica has made key product announcements that will impact its future and the future of data management.
Topics: Big Data, Data Quality, Master Data Management, MDM, Operational Performance Management (OPM), Cloud Computing, Data Integration, Data Management, Data Preparation, Governance, Risk & Compliance (GRC), Informatica, Information Management, Business Performance Management (BPM), Information Optimization, Risk & Compliance (GRC)
Datawatch Bolsters Data Preparation for all Information Assets
The need for businesses to process and analyze data has grown in intensity along with the volumes of data they are amassing. Our benchmark research consistently shows that preparing data is the most widespread impediment to analytic and operational efficiency. In our recent research on data and analytics in the cloud, more than half (55%) of organizations said that preparing data for analysis is a major impediment, followed by other preparatory tasks: reviewing data for quality and consistency (48%) and waiting for data and information (28%). Organizations that want to apply analytics to make more effective decisions and take prompt actions need to find ways to shorten the work that comes before it. Conventional analytics and business intelligence tools are not designed for data preparation, but new software tools can enable business users independently or in concert with IT to perform the tasks needed.
Topics: Big Data, Sales Performance, Supply Chain Performance, Human Capital, Marketing, Monarch, Operational Performance Management (OPM), Customer Performance, Business Analytics, Business Intelligence, Business Performance, Data Preparation, Financial Performance, Governance, Risk & Compliance (GRC), Information Management, Uncategorized, Business Performance Management (BPM), Datawatch, Information Optimization, Risk & Compliance (GRC)
Pentaho Poised for Exploiting Internet of Things
PentahoWorld 2015, Pentaho’s second annual user conference, held in mid-October, centered on the general availability of release 6.0 of its data integration and analytics platform and its acquisition by Hitachi Data Systems (HDS) earlier this year. Company spokespeople detailed the development of the product in relation to the roadmap laid out in 2014 and outlined plans for its integration with those of HDS and its parent Hitachi. They also discussed Pentaho’s and HDS’s shared intentions regarding the Internet of Things (IoT), particularly in telecommunications, healthcare, public infrastructure and IT analytics.
Topics: Big Data, Pentaho, Mobile Technology, Wearable Computing, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, IOT, Operational Intelligence, Uncategorized, Information Optimization, Risk & Compliance (GRC)
The State of Product Information Management Software for Business and IT
The importance of product information management (PIM) has become clear in recent years and especially as it relates to master data management. As I recently wrote handling this business process effectively and using capable software should be priorities for any organization in marketing and selling its products and services but also interconnecting the distributed supply chain. Our research on product information management can help organizations save time and resources in efforts to ensure that product information is an asset to facilitate efficiency in many business processes. Through years of benchmarking, we have developed a blueprint for managing and improving product information. Using this approach enables companies to more effectively align and link their activities and processes. Of course achieving effectiveness also requires using applications that create consistent, reliable product information. We regularly update our Value Index for PIM to enable companies to evaluate vendors and their applications’ suitability for use in all business processes requiring product information.
Topics: Big Data, Master Data Management, Sales Performance, Supply Chain Performance, Enterworks, Marketing, Operational Performance Management (OPM), Stibo Systems, Webon, Business Performance, CIO, Financial Performance, IBM, Informatica, Information Management, Oracle, Information Optimization, Product Information Management, Riversand
Product Information Management Trumps Master Data Management
Ventana Research defines product information management (PIM) as the practice of using information, applications and other technology to effectively support product-related processes across the customer, commerce and supply chain. As organizations increase the number and diversity of products and services they offer to customers and partners, they increasingly need to address limitations in the ways they manage and distribute product information, including related attributes and content that describes the products. At the same time, competitive pressures require them to be able to incorporate large amounts of new content – video and images, for example – quickly while ensuring that the information presented to customers is accurate, operational processes run uninterrupted and timely data is available for business analysis. In an environment in which consumers, suppliers and partners use multiple channels to get to product information – including websites, kiosks, smartphones and tablets – it is essential that the organization always be able to present complete and up-to-date product information to inspire interest and facilitate purchases.
Topics: Big Data, Master Data Management, Supply Chain Performance, Governance, Marketing, Operational Performance Management (OPM), CIO, Information Management, Business Performance Management (BPM), Financial Performance Management (FPM), Information Optimization, Product Information Management, Sales Performance Management (SPM)
Splunk Takes on Internet of Things and Bolsters Enterprise Security
Splunk’s annual gathering, this year called .conf 2015, in late September hosted almost 4,000 Splunk customers, partners and employees. It is one of the fastest-growing user conferences in the technology industry. The area dedicated to Splunk partners has grown from a handful of booths a few years ago to a vast showroom floor many times larger. While the conference’s main announcement was the release of Splunk Enterprise 6.3, its flagship platform, the progress the company is making in the related areas of machine learning and the Internet of Things (IoT) most caught my attention.
Topics: Big Data, Predictive Analytics, Machine Learning, IT Analytics & Performance, Operational Performance, Plunk, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Management, Internet of Things, Operational Intelligence, Data, Information Optimization
The concept and implementation of what is called big data are no longer new, and many organizations, especially larger ones, view it as a way to manage and understand the flood of data they receive. Our benchmark research on big data analytics shows that business intelligence (BI) is the most common type of system to which organizations deliver big data. However, BI systems aren’t a good fit for analyzing big data. They were built to provide interactive analysis of structured data sources using Structured Query Language (SQL). Big data includes large volumes of data that does not fit into rows and columns, such as sensor data, text data and Web log data. Such data must be transformed and modeled before it can fit into paradigms such as SQL.
Topics: Big Data, Predictive Analytics, Software as a Service, IT Analytics & Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Management, Operational Intelligence, Data, Information Optimization
Operationalize Predictive Analytics for Significant Business Impact
One of the key findings in our latest benchmark research into predictive analytics is that companies are incorporating predictive analytics into their operational systems more often than was the case three years ago. The research found that companies are less inclined to purchase stand-alone predictive analytics tools (29% vs 44% three years ago) and more inclined to purchase predictive analytics built into business intelligence systems (23% vs 20%), applications (12% vs 8%), databases (9% vs 7%) and middleware (9% vs 2%). This trend is not surprising since operationalizing predictive analytics – that is, building predictive analytics directly into business process workflows – improves companies’ ability to gain competitive advantage: those that deploy predictive analytics within business processes are more likely to say they gain competitive advantage and improve revenue through predictive analytics than those that don’t.
Topics: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
Business Case for Predictive Analytics is Simpler Than You Think
Our benchmark research into predictive analytics shows that lack of resources, including budget and skills, is the number-one business barrier to the effective deployment and use of predictive analytics; awareness – that is, an understanding of how to apply predictive analytics to business problems – is second. In order to secure resources and address awareness problems a business case needs to be created and communicated clearly wherever appropriate across the organization. A business case presents the reasoning for initiating a project or task. A compelling business case communicates the nature of the proposed project and the arguments, both quantified and unquantifiable, for its deployment.
Topics: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
Data and Analytics in the Cloud is a Reality Today
Our recently completed benchmark research on data and analytics in the cloud shows that analytics deployed in cloud-based systems is gaining widespread adoption. Almost half (48%) of participating organizations are using cloud-based analytics, another 19 percent said they plan to begin using it within 12 months, and 31 percent said they will begin to use cloud-based analytics but do not know when. Participants in various areas of the organization said they use cloud-based analytics, but front-office functions such as marketing and sales rated it important more often than did finance, accounting and human resources. This front-office focus is underscored by the finding that the categories of information for which cloud-based analytics is most often deemed important are forecasting (mentioned by 51%) and customer-related (47%) and sales-related (33%) information.
Topics: Big Data, Software as a Service, Operational Performance Management (OPM), Analytics, Business Analytics, Business Collaboration, Business Intelligence, Customer & Contact Center, Operational Intelligence, Business Performance Management (BPM), Data, Information Optimization
Data Preparation is Essential for Predictive Analytics
Our research into next-generation predictive analytics shows that along with not having enough skilled resources, which I discussed in my previous analysis, the inability to readily access and integrate data is a primary reason for dissatisfaction with predictive analytics (in 62% of participating organizations). Furthermore, this area consumes the most time in the predictive analytics process: The research finds that preparing data for analysis (40%) and accessing data (22%) are the parts of the predictive analysis process that create the most challenges for organizations. To allow more time for actual analysis, organizations must work to improve their data-related processes.
Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence, Oracle, Information Optimization
Skills Gap Challenges Potential of Predictive Analytics
The Performance Index analysis we performed as part of our next-generation predictive analytics benchmark research shows that only one in four organizations, those functioning at the highest Innovative level of performance, can use predictive analytics to compete effectively against others that use this technology less well. We analyze performance in detail in four dimensions (People, Process, Information and Technology), and for predictive analytics we find that organizations perform best in the Technology dimension, with 38 percent reaching the top Innovative level. This is often the case in our analyses, as organizations initially perform better in the details of selecting and managing new tools than in the other dimensions. Predictive analytics is not a new technology per se, but the difference is that it is becoming more common in business units, as I have written.
Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Operational Performance Management (OPM), Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Location Intelligence, Oracle, Information Optimization
Big Data Analytics Will Displace Net Promoter Score (NPS) for Measuring Customer Experience
Our benchmark research into big data analytics shows that marketing in the form of cross-selling and upselling (38%) and customer understanding (32%) are the top use cases for big data analytics. Related to these uses, organizations today spend billions of dollars on programs seeking customer loyalty and satisfaction. A powerful metric that impacts this spending is net promoter score (NPS), which attempts to connect brand promotion with revenue. NPS has proven to be a popular metric among major brands and Fortune 500 companies. Today, however, the advent of big data systems brings the value and the accuracy of NPS into question. It and similar loyalty metrics face displacement by big data analytics capabilities that can replace stated behavior and survey-based attitudinal data with actual behavioral data (sometimes called revealed behavior) combined with unstructured data sources such as social media. Revealed behavior shows what people have actually done and thus is a better predictor of what they will do in the future than what they say they have done or intend to do in the future. With interaction through various customer touch points (the omnichannel approach) it is possible to measure both attitudes and revealed behavior in a digital format and to analyze such data in an integrated fashion. Using innovative technology such as big data analytics can overcome three inherent drawbacks of NPS and similar customer loyalty and satisfaction metrics.
Topics: Big Data, Customer Performance, Business Analytics, Business Performance, Operational Intelligence, Information Optimization
Data is an essential ingredient for every aspect of business, and those that use it well are likely to gain advantages over competitors that do not. Our benchmark research on information optimization reveals a variety of drivers for deploying information, most commonly analytics, information access, decision-making, process improvements and customer experience and satisfaction. To accomplish any of these purposes requires that data be prepared through a sequence of steps: accessing, searching, aggregating, enriching, transforming and cleaning data from different sources to create a single uniform data set. To prepare data properly, businesses need flexible tools that enable them to enrich the context of data drawn from multiple sources, collaborate on its preparation to serve business needs and govern the process of preparation to ensure security and consistency. Users of these tools range from analysts to operations professionals in the lines of business.
Topics: Big Data, Sales Performance, Supply Chain Performance, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Data Preparation, Financial Performance, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Information Optimization
Big Data Research Agenda and Trends are Bolder in 2015
Big data has become a big deal as the technology industry has invested tens of billions of dollars to create the next generation of databases and data processing. After the accompanying flood of new categories and marketing terminology from vendors, most in the IT community are now beginning to understand the potential of big data. Ventana Research thoroughly covered the evolving state of the big data and information optimization sector in 2014 and will continue this research in 2015 and beyond. As it progresses the importance of making big data systems interoperate with existing enterprise and information architecture along with digital transformation strategies becomes critical. Done properly companies can take advantage of big data innovations to optimize their established business processes and execute new business strategies. But just deploying big data and applying analytics to understand it is just the beginning. Innovative organizations must go beyond the usual exploratory and root-cause analyses through applied analytic discovery and other techniques. This of course requires them to develop competencies in information management for big data.
Topics: Big Data, MapR, Predictive Analytics, Sales Performance, SAP, Supply Chain Performance, Human Capital, Marketing, Mulesoft, Paxata, SnapLogic, Splunk, Customer Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Cloudera, Financial Performance, Hortonworks, IBM, Informatica, Information Management, Operational Intelligence, Oracle, Datawatch, Dell Boomi, Information Optimization, Savi, Sumo Logic, Tamr, Trifacta, Strata+Hadoop
The market for big data continues to grow as organizations try to extract business value from their own masses of data and other sources. Earlier this year I outlined the dynamics of the business opportunity for big data and information optimization. We continue to see advances as big data and associated information technologies deliver more value, but the range of innovation also has created fragmentation among existing systems including databases that are managed onpremises or in cloud computing environments. In this changing environment organizations encounter new challenges not only in adapting to technology that is more efficient in automating data processing but also in integrating it into their enterprise architecture. I’ve already explained how big data can be ineffective without integration, and we conducted more in-depth research into the market, resulting in our benchmark research on big data integration, which reveals the state of how organizations are adopting this technology in their processes.
Topics: Big Data, Business Analytics, Information Applications, Information Management, Information Optimization
Informatica Unveils New Platform and Tools for Information Optimization
At the Informatica World 2014 conference, the company known for its data integration software unveiled the Intelligent Data Platform. In the last three years Informatica has expanded beyond data integration and now has a broad software portfolio that facilitates information management within the enterprise and through cloud computing. The Intelligent Data Platform forms a framework for its portfolio. This expression of broad potential is important for Informatica, which has been slow to position its products as capable of more than data integration. A large part of the value it provides lies in what its products can do to help organizations strengthen their enterprise architectures for managing applications and data. We see Informatica’s sweet spot in facilitating efficient use of data for business and IT purposes; we call this information optimization.
Topics: Big Data, Master Data Management, Sales Performance, Supply Chain Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Data Integration, Data Management, Financial Performance, Informatica, Information Applications, Information Management, Workforce Performance, Information Optimization, Product Information Management, application
The Business Technology Challenge of 2014: Information Optimization
Our recently released benchmark research on information optimization shows that 97 percent of organizations find it important or very important to make information available to the business and customers, yet only 25 percent are satisfied with the technology they use to provide that access. This wide gap between importance and satisfaction reflects the complexity of preparing and presenting information in a world where users need to access many forms of data that exist across distributed systems.
Topics: Big Data, IT Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Data Preparation, Information Applications, Information Management, Data Discovery, Datawatch, Information Optimization
Big Data Offers Business Opportunity for Information Optimization in 2014
Businesses are always looking for ways to grow and to streamline their operations. These two goals can come into conflict because as organizations become larger it becomes more complicated to be agile and efficient. To help them understand and modify their processes, businesses can derive insights from analytics applied to their data. Today that data is available not only in the enterprise and cloud computing environments but also from the Internet. To collect, process and analyze it all is a challenge, one that an increasing number of organizations are meeting through the use of big data technologies. The resulting insights can help them make strategic business decisions such as where to focus efforts and how to engage with customers. At Ventana Research we have been working hard to understand the advancing technology that supports big data and its value through information optimization and bring clarity to the industry through our research and analysis of trends and products. There are many opinions about big data and fixation on the attributes of it through the V’s (volume, variety and velocity) and how to use it, often biased toward one technology or vendor; our research and analysis of the entire market cuts through the noise to provide not just facts but insights on best practices and methods to apply this technology to business problems.
Topics: Big Data, Sales Performance, Social Media, Supply Chain Performance, IT Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Information Optimization
Ventana Research Technology Innovation Awards Are More Than Cool
In the realm of technology that matters for business and IT, our firm as part of our responsibility continually assesses the latest technology and how it can impact organizations’ efficiency and effectiveness. Our benchmark research in technology innovation found that 87% of participants indicated the importance of increasing the organization’s value through technology innovation. Every year we take our knowledge from research and technology briefings to focus on our Technology Innovation Awards and determine the vendors and products that have the potential to drive change in the market, the competitiveness of an organization’s business and sometimes just how efficiently a company operates. Our firm believes that Innovation can come from any size technology vendor from the smallest to the largest that are measured on a spectrum of attributes that contribute to the specific impact of the technology.
Topics: Big Data, Datameer, Mobile, Sales, Sales Performance, Social Media, Supply Chain Performance, Sustainability, Customer, ESRI, Globoforce, GRC, HCM, Kronos, Kyriba, Location Analytics, Marketing, NetBase, Office of Finance, Overall Operational Leadership, Peoplefluent, Planview, SQLstream, VMWare, VPI, IT Analytics & Performance, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, CIO, Cloud Computing, Collaboration, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), Hortonworks, IBM, Informatica, Information Applications, Information Builders, Information Management, Information Technology, KXEN, Location Intelligence, Operational Intelligence, Oracle, Workforce Performance, Contact Center, Datawatch, Financial Management, Information Optimization, Johnson Controls Panoptix, Roambi, Service & Supply Chain, Upstream Works, Vertex, Xactly
Cisco to Foster Smarter Network of Data by Acquiring Composite Software
Cisco Systems has announced its intent to acquire Composite Software, which provides data virtualization to help IT departments interconnect data and systems; the purchase is scheduled to complete in early August. Cisco of course is known for its ability to interconnect just about anything with its networking technology; this acquisition will help it connect data better across networks. Over the last decade Composite had been refining the science of virtualizing data but had reached the peak of what it could do by itself, struggling to grow enough to meet the expectations of its investors, board of directors, employees, the market and visionary CEO Jim Green, who is well-known for his long commitment to improving data and technology architectures. According to press reports on the Internet, Cisco paid $180 million for Composite, which if true would be a good reward for people who have worked at Composite for some time and who were substantive shareholders.
Topics: Big Data, Networking, IT Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Data Management, Information Applications, Information Management, Cisco, Composite Software, Data, Data Virtualization, Information Optimization, Internet of Everything, Strata+Hadoop
Datawatch Acquires Panopticon for Big Data Discovery and Visualization across Business Processes
Business analytics can help organizations use data to find insights that lead to new opportunities and address issues unrecognized before. One player in this market is Datawatch, known for its tools for information optimization and harvesting value from big data including content and documents. I assessed the company earlier this year, and recently our firm recognized its customers’ achievements with 2013 Ventana Research Leadership Awards for Information Optimization with Phelps County Regional Medical Center and Governance, Risk and Compliance (GRC) with The Fauquier Bank.
Topics: Big Data, Sales Performance, SAP, Supply Chain Performance, GRC, Office of Finance, Panopticon, Operational Performance, Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Information Applications, Information Management, Operational Intelligence, CEP, Datawatch, Discovery, Information Optimization, SAP HANA
Informatica Has New Vibe for Information Optimization
Information management is important to every line of business that seeks to improve its business processes and decision-making. In response to pressure from those departments, CIOs and IT organizations must examine whether they have focused enough on the I for information and not just the T for technology, and if they have not, commit to taking this responsibility more seriously than in the past. Informatica is one vendor that realizes the potential of its information beyond just data integration, and this is reflected in its expanded product portfolio and position in the market over the last several years. Our firm has taken note of companies gaining value from using Informatica; we awarded our 2013 CIO Leadership Award to George Brenckle of UMass Memorial Health Care for his work to maximize the value of information assets through managing data innovatively. Informatica itself has enhanced its position by introducing its new brand and a new CMO and demonstrating commitment to change from its executive leadership team at the company’s recent 2013 user conference. The focus of the brand now is on helping business and IT find the full value of their information.
Topics: Data Quality, Master Data Management, PowerCenter, Operational Performance, Analytics, Business Analytics, Business Performance, CIO, Cloud Computing, Data Integration, Information Applications, Information Management, Information Optimization, Vibe
Datawatch Enables a New Generation of Information Optimization
When organizations need to optimize their business processes and improve operations and decisions, the often speak of having the right information at the right time, but don’t always make that a priority. This information optimization is often thought to be expensive and time-consuming, especially with advent of big data and disparate data sources across cloud and on-premises environments, as I have articulated. Datawatch can help business get to information of any variety or volume at any time through its access and integration tools. When I published my last analysis of Datawatch, it had made significant advancements in its platform, with enterprise-class reliability and support for business analytics through its data discovery and virtualization processes. Over the last year Datawatch continued to grow its business worldwide, and through investments into its marketing, sales and product efforts is finding more potential from existing and new customers. The company’s energized product efforts earned it our 2012 Technology Innovation Award for Information Applications for its Information Optimization Suite.
Topics: Big Data, MapR, QlikView, Cloud Computing, Information Management, Uncategorized, Datawatch, Information Optimization
Businesses Can Turn to Scribe for Integration in the Cloud Anytime
Businesses continue to try to increase productivity and simplify tasks in order to use their time smarter. Our recent business technology innovation research found that, when it comes to analytics, 44 percent of organizations spend the most time on data-related tasks. With lack of resources being the largest issue impeding the adoption of technology, IT must operate efficiently while getting business the data it needs on a timely basis. Scribe Solutions has a business-centric data integration solution that operates in the cloud. Over the last 15 years Scribe has accumulated more than 12,000 customers worldwide that span from Fortune 500 to midsize to small organizations. Scribe enables business to access marketing and sales data (part of CRM) like that in Microsoft Dynamics. It has built a strong presence indirectly and through Microsoft partners; it claims to have more than 1,000 partners, and has been expanding efforts to broaden its position by supporting a range of data sources, including Salesforce.com. Scribe focuses on what I call information optimization, providing value from information management investments, as I outlined in our research agenda.
Topics: Microsoft, Sales Performance, Marketo, On24, SilverPop, IT Performance, Operational Performance, Business Intelligence, Business Performance, Customer & Contact Center, Data Integration, Information Applications, Information Management, FinancialForce, Information Optimization, Intuit Quicken, Scribe Software, Xactly
The Big Deal with Big Data is More Valuable with Kapow
Using information from applications and services across both the enterprise and Internet just got simpler with Kapow Software and the announced release of Kapow Enterprise 9.2. I examined the technology at the Kapow WoW user conference, and spoke with a broad range of companies that use Kapow.
Topics: Big Data, Sales Performance, Supply Chain Performance, Kapplets, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Information Applications, Information Management, Information Optimization, Kapow
Information Optimization is a Key Benefit of Big Data Investments
Data is a commodity in business. To become useful information, data must be put into a specific business context. Without information, today’s businesses can’t function. Without the right information, available to the right people at the right time, an organization cannot make the right decisions nor take the right actions, nor compete effectively and prosper. Information must be crafted and made available to employees, customers, suppliers, partners and consumers in the forms they want it at the moments they must have it. Optimizing information in this manner is essential to business success. Yet I see organizations today focusing on investments in big data because they believe it can effortlessly bring analysts insights. That premise is incorrect.
Topics: Big Data, Analytics, Business Analytics, Cloud Computing, In-Memory Computing, Information Applications, Information Management, Information Optimization, Strata+Hadoop, Digital Technology