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The platform enables any data worker to turn the tremendous potential of data into something real and actionable faster than before. Thousands of companies of all sizes experience the thrill of solving game-changing problems using Alteryx. With a vibrant online and offline community, everyone from business analysts to data scientists are loving their jobs again because of the Alteryx platform. The platform is flexible enough to harness the power of data for a competitive edge and deliver real business impact.
In the past twelve months, Alteryx has introduced several new solutions that help round out the end-to-end platform—from data discovery to prep and blending, to visualization and insights. These solutions include:
• Alteryx Connect—a data exploration platform that allows users to discover and collaborate on data assets, and workflow visualizations, etc. that are typically siloed across departments. It is an outgrowth of the company’s acquisition of Semanta in early 2023.
• Alteryx Promote: a component of the Alteryx platform that empowers both data scientists and citizen data scientists to deploy predictive models directly into business systems through an API and then managing model performance over time. It is the result of the Alteryx’s acquisition of Yhat, a Brooklyn-based data science company, announced in June 2023.
A Dynamic Leader Who Knows the Way
Dean Stoecker is the Chairman, Chief Executive Officer, and a Founding Partner of Alteryx. Dean’s leadership and motivational skills, along with his ability to create, communicate and realize a vision, are a driving force behind bringing back the thrill of solving to analysts and data scientists across the globe.
Alteryx is a 20-year success story with Stoecker leading the company through solid organic growth, three rounds of funding and a successful IPO in March of 2023 to deliver a transformational experience to customers of all sizes. Dean’s unique vision and strategy around bringing a code-free and code-friendly experience unleashes the line-of-business analyst from the menial and mundane to truly loving their work again.
2023 was a banner year for the company. In addition to being recognized as one of the top performers in the class of 2023 IPOs, Stoecker received the EY Entrepreneur of The Year® 2023 Award in the Orange County Region, which recognizes entrepreneurs who excel in areas such as innovation, financial performance and personal commitment to their businesses and communities. In addition, Dean drives a philanthropic leadership with the creation of Alteryx for Good, a program that brings the charge of solving real-world problems to non-profits, educators, and local communities.
Success Doesn’t Come Overnight
Dean has said, “You can live without an arm or a leg, but you can’t live without a heart; analytics is the heart of the enterprise.” Alteryx’s rise to success is not your typical Silicon Valley story. Based in Irvine, CA., the 20-year-old company was founded as SRC in 1997 before changing its name to Alteryx in 2010. Dean and the rest of the co-founders never took a dollar of venture money until 2011. Alteryx ultimately raised US$163 million in three rounds, when Dean saw an opportunity for growth and a broader vision for an IPO.
Client Satisfaction at the Forefront
Alteryx has earned the trust of thousands of customers around the world, ranging from many of the world’s largest and best-known brands, including Kaiser, Ford, and McDonald’s, to growing organizations such as Rosenblatt Securities, Veritix, and Consumer Orbit, who all want to use the power of data for a competitive edge.
Awards and Recognition
Alteryx has been honored by several organizations for company growth, customer satisfaction, and impact on the industry and community. A few notable awards include:
Alteryx was traditionally known for its data prep and blending capabilities and the company is tasked with changing that perception. Its technology has evolved to a complete, end-to-end analytics platform, from data discovery to prep and blending, to visualization and insights.
Future Industry Predictions
Alteryx will continue to build its platform with the goal of revolutionizing businesses through data science and analytics. Below are a few predictions on where the data analytics industry is heading in general:
• Data science will break free from code-dependence. The company sees increased adoption of common frameworks for encoding, managing and deploying machine learning and analytical processes. The value of data science will become less about the code itself and more about the application of techniques. As analytics becomes more pervasive in organizations, and the number of data sources and statistical languages (R, Python, Scala, etc.) continues to expand and evolve, the industry will see the need for a common, code-agnostic platform where LOB analysts and data scientists alike can preserve existing work and build new analytics going forward.
• The CDO will come of age. Data is essentially the new oil, and the CDO is beginning to be recognized as the lynchpin for tackling one of the most important problems in enterprises today – driving value from data. Often with a budget of less than US$10 million, one of the biggest challenges and opportunities for CDOs is making the much-touted self-service opportunity a reality by bringing corporate data assets closer to line-of-business users. In 2023, the CDOs that work to strike a balance between a centralized function and capabilities embedded in LOB will ultimately land the larger budgets. Success will come to CDOs who put greater focus on agile platforms and methodologies that allow resources, skills, and functionality to shift rapidly between CoE and LOB.
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Web site analytics provide valuable information about who is coming to your site and what they do once they get there. At the simplest level, a counter that displays the number of visitors to a page is a source of Web analytics, but analytics when interpreted properly, is much more than that. Knowing information about your site visitors and the actions they take can help you determine some important factors.
Many Web hosts provide a degree of analytical reporting as part of their service, but generally these are lacking in the amount of information they provide. For a single-page fledgling site they may provide enough information, but for a multiple page catalog you’ll need more. It isn’t necessary to pay large amounts for a service, though, and free services such as the highly-rated StatCounter provide an excellent basis from which to begin your analytical journey. Generally speaking, they all provide similar data, which can be used in the following ways:
By closely monitoring the keywords people use to find your site it is possible to adapt your service and your site to match their needs more closely. If searchers entering specific search strings are visiting your site then you know the kind of information they are seeking. It is possible to alter and optimize your pages, your products, and even your offers to increase revenue and performance.
Second, these statistics also offer a method of determining which of your visitors are more likely to purchase. In most cases, the more specific a search term or the more targeted a link, the more likely a person is to eventually purchase through your site. Because the visitor path displays the way a visitor found your site and shows if they made it to “checkout” or not, you can soon determine the most responsive sources of traffic.
A good way to encourage people to spend more money on your site is to offer them “related product” links. On product pages you can place links to related items that they may be interested in and the visitor path information is the ideal way to find the perfect combination of products.
Less than 5 seconds
Between 5 and 30 seconds
Between 30 seconds and 5 minutes
Between 5 minutes and 20 minutes
Between 20 minutes and 1 hour
Longer than an hour
Hopefully you will witness a small percentage of people that remain on your site for less than five seconds, but in reality it will depend on how targeted your traffic is. Well-targeted traffic is more likely to remain on the pages of your site whereas poorly targeted traffic will leave if not immediately interested.
Take a closer look at visitors that leave quickly and determine where they came from. If a PPC ad is providing you with visitors that only look at the resulting page and then leave, that’s an area you should spend time studying. Letting a poor-performing PPC campaign go unevaluated is one of the quickest ways lose money.
System statistics includes information like the browser that each of your visitors uses, or the resolution of their screen size, the operating system they use, and even whether their browser is Java enabled. This is invaluable for ensuring that all of your visitors are able to effectively view your site and provides you with potential reasons for any unusual activity on your pages.
While Internet Explorer is usually the browser of choice for 50 percent or more of site visitors, that still leaves a lot of shoppers using Firefox and other browser alternatives. If your site has only been tested in Internet Explorer and does not display correctly in other browsers, you could be losing as many as half of your potential customers.
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Data science can add value to any business that uses it well. From finding statistics and insights across workflows to hiring new candidates and helping staff make better-informed decisions, data science is valuable to any company in any industry. The biggest reason for its looming popularity is its ability to allow brands to communicate their story in an engaging and powerful manner. When brands and companies comprehensively utilize data, they can share their goal with their target audience, thereby creating better brand connections. After all, nothing connects with consumers like an effective and powerful story that can inculcate all human emotions. Precisely, Data science algorithms help perform complex data science tasks like prediction, classification, clustering, and others. Paving the way for the success of businesses through its values,An Accomplished Big Data Leader Deciphering Business Challenges
Hill Climbing Algorithm: This algorithm boosts model performance. It searches for the optimal subset of features from a given list, subject to a user-defined performance metric as its objective function. The procedure uses the hill-climbing iterative modeling process by evaluating all combinations of n features before climbing up to n+1. Super Interactions: This algorithm captures non-linear relationships. It explores all possible n-way combinations of interactions. For n = 2 through 5, just 50 raw features can form over 2 million new variables! The procedure is suitably coupled with effective and efficient variable reduction techniques. Segmentation Recommender: The segmentation recommender algorithm enables data segmentation decision-making. It evaluates a set of pre-defined strategic scenarios on given data and makes a recommendation for a single overall model or multiple-segmented models. The procedure blends business needs with statistical tests such as correlation sign flip, over-dependence on a specific predictor, and error pattern analysis. Feature Clustering Enhancer: This algorithm selects predictive and representative features. It recommends variable selection based on joint analysis of unsupervised feature clustering outcome and supervised association analysis. The procedure provides flexibility to shortlist the top variables from each category. Statistical Model Assessment and Review Tool (S.M.A.R.T.): This is a .Net and SQL-based analytics product that serves as a one-stop-shop solution for model monitoring. Key features include a dashboard with multi-level views, on-demand monitoring, scheduler, model governance, and fully automated model assessment. Such analytics accelerators have translated into faster and improved outcomes at scale for Varun’s clients, thereby creating “speed to value” differentiation and enabling better decisions for the data-led businesses.Denting the Digital Space with Data Science Contributions
Varun has contributed to the data analytics field not only in the capacity of an individual consultant but also by leading large teams comprising 200+ data scientists and by training 1000+ analytics professionals on predictive modeling. In fact, he designed and authored a comprehensive data science methodology training course that feeds into his organization’s flagship training program for new hires.Data Segmentation
Should I Build a Segmented Model? A Practitioner’s Perspective, NYASUG Conference, January 14, 2010, Pace University, NY, USFeature Engineering and Feature Selection
PROC LOGISTIC Plus: The Power of Variable Transformations, NESUG Conference, September 14-17, 2008, Pittsburgh, PA, US
Feature Selection and Dimension Reduction Techniques in SAS, NESUG Conference September 11-14, 2011, Portland, ME, US
Feature Engineering Strategies: A Practitioner’s Guide, 5th IIMA International Conference on Advanced-Data Analysis, Business Analytics, and Intelligence, April 8-9, 2023, Ahmedabad, IndiaModel Training
Ensemble Hybrid Logit Model, KDD Cup 2010, Educational Data Mining Challenge, hosted by PSLC DataShop, July 2010
Solving the CECL Riddle through Risk Analytics, 6th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, April 6-7, 2023, Ahmedabad, India
Credit Card Fraud Detection using Feature Engineering and Machine Learning, presented at Machine Learning Developers Summit 2023 organized by Analytics India Magazine and published by Association of Data Scientists, Lattice, The Machine Learning Journal, Volume-3, Issue-1, JanuaryMarch 2023Model Validation
Retail Credit Risk Model Validation: Performance and Stability Aspects, 4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence, April 11-12, 2023, Ahmedabad, India
In addition, Varun has co-authored a series of EXL white papers on credit loss forecasting.Advanced Analytics at the Heart of Innovation
Leading digital analytics experts share their examples of how to effectively use data and analytics to generate actionable insights for your marketing strategy
The number of data sources that are available is growing every day. For some of us, this might be a good thing, but for many digital marketers it brings up a lot of challenges to deal with. With increased data, it can be easy to lose focus, become obsessed by ‘vanity metrics’, and fail to generate actionable insights for your business.
McKinsey notes that surges in data caused by rapid digital disruption have not ‘provided marketers with a substantially better understanding of their customers, because their companies’ outdated data modeling isn’t able to capture these shifts with the necessary granularity and speed’.
So, while the innovators are leading the way with actionable analytics feeding their data-driven marketing, others become stagnant. In today’s competitive marketing landscape, this means losing market share, and customers, to your competitors. You don’t want that, that’s why we’ve got 10 tactics to help get you back on track.Unlock actionable, practical strategy with the RACE Framework
That’s where our RACE Framework comes in. The RACE Framework empowers markers and managers to break down their customer journey across the 5-step RACE structure of plan – reach – act – convert – engage. Within each stage, we will guide you to set objectives, and measure the metrics and KPIs necessary to achieve your goals.
Need a winning marketing strategy?
Book your free 1-2-1 consultation to develop your new strategy with the RACE Framework
Book consultationReporting vs. analysis
The job of a digital marketer and analyst is not to come up with a lot of fancy-looking reports that contain tons of data. In my opinion, data is just input. The insights you provide should be your most important output.
~ W.E.B. Du Bois
You need to answer what the numbers mean to your business and what action should be taken to improve the most important metrics of the business.Turn data into actionable insights
I have worked with many companies that really got stuck here. Being able to collect the right data is one thing, but making it extremely useful requires a different skill- and mindset.
We’ve got marketing solutions to help you boost your use of data and analytics to inform your marketing strategy. Our marketing tools and templates are integrated across the RACE Framework, so you can apply a data-driven approach to planning, managing, and optimizing your customers’ journeys.
Find out more about how your company can benefit from Business Membership by booking on your free 1-2-1 marketing strategy consultation call. Our calls help you experience our bespoke services for businesses, kicking off by identifying opportunities for growth across your customer lifecycle using the RACE Framework.Need a winning marketing strategy?
Book your free 1-2-1 consultation to develop your new strategy with the RACE Framework
Book consultationExamples of actionable insights
Leading digital analytics experts share their examples of how to effectively use data and analytics to generate actionable insights for your marketing strategy1. Measure the right things
You can’t optimize what you don’t measure. There is not a one-size-fits-all solution. Every business is different and should be treated in a unique way.
Let’s assume you run an e-commerce site. In this case, here are some examples of what you probably want to know:
Which channels drive the most conversions?
What are your leaking buckets (places where people leave your website)?
Whether people use multiple devices before purchasing your products?
What are the look-to-buy ratios for your individual products and product categories?
What landing pages need to be improved and in which channel?2. Ask the right questions to stakeholders
Go the extra mile to answer all of your stakeholder’s questions. This means tapping into the stakeholderís aspirations and challenges by asking the right questions.
Examples of marketing insights that could add value for your stakeholders:
Outlining specific events and general trends to support your strategy
Critical environmental and competitor scanning, and market research
Commercial insights and ROI
You can easily waste hours of your time by getting lost in your data. And coming up with “insights” that are already known or not deemed important can be highly frustrating as well! By ascertaining your stakeholders’ expectations for actionable insights.
Need a winning marketing strategy?
Book your free 1-2-1 consultation to develop your new strategy with the RACE Framework
Book consultation3. Use segmentation to drive action
Go for segmentation if you want to take action on your data! By grouping visitors that have some attributes in common, you can start digging deeper. Choosing which segments to study depends on the business question you are trying to answer.
Identifying segments will greatly enhance your understanding of how your customers behave. You can use this information for setting up an optimization plan.
Digital analytics tools like Google Analytics come with a lot of built-in segments and provide you with all the freedom to customize them to your needs.4. Use clear visualizations to convey your message
The way in which you present your data will make a huge difference in the outcome. Do you remember these presentations that only include numbers and words? And this compared to clear visualizations that promote cognition instead of confusion.
It’s important to articulate a data story with as much what, how, and why behind it. This will turn your data into insights and profitable business decisions.5. Discover the context of your data set
Make sure to establish context for the data you are seeing. Examples of data contextualizing questions include:
What do these numbers mean?
Are they important?
Does it really affect the business?
And how is the data collected?
Data without context isn’t that meaningful and can actually lead to bad business decisions because of interpreting it in the wrong way!
Digital strategy success factors
Part of the Digital marketing strategy and planning Toolkit
Learn how to define a structure and scope for your omnichannel marketing strategy
Learn More6. Build a solid optimization plan
Use the “Define Measure Analyze Improve Control” process (DMAIC) to improve your business. It’s one of the Six Sigma concepts you can directly apply in your situation.
Embracing the notion of continuous improvement, we continually aim for the identification and implementation of best practices and work to move closer towards perfect solutions for inefficiencies and imperfect processes.
In short, it comes down to:
Define the problem or hypothesis, stakeholders and scope of analysis.
Measure relevant data and conduct basic analysis to spot anomalies.
Analyze correlations and patterns, put your statistics and visualization skills to work.
Improvement based on insights and showing several options to explore.
Control the change by deploying (A/B) tests and monitoring KPIs.7. Construct a great hypothesis
Formulating these statements isn’t always easy, but you will save a ton of time wandering through your data and coming up with interesting – but not actionable – findings.8. Integrate data sources
Structure a plan using Smart Insights’ RACE
Part of the Digital marketing strategy and planning Toolkit
Learn how to structure a comprehensive omnichannel marketing plan, using Smart Insights’ RACE
Learn More9. Break down organizational silos
A healthy organization is the foundation of everything. Communication instead of confrontation. Inspire, motivate and be curious about the data and the possibilities it has for your organization. Treat any obstacles first and improve the communication between the business and analytics leaders.10. Don’t forget to hire smart people
Tools can collect data, but people – who understand the business – build insights. Smart people are required to find useful data, translate it into data-driven stories of useful knowledge – the insights. It’s a team effort where combining internal business experts with external analysts might be your best bet.Strategize for actionable insights
Each of the tactics described above can help you fine-tune your action plan for turning data into actionable insights and profits for your business. You might want to pick a few tactics and first experiment with them. Find out what works best in your industry and situation and go from there.
While Palantir has a bad reputation for its role in USA immigration scheme, it has received huge market acceptance recently.
There are many data analytics companies that have dominated the industry with their key offerings. Two popular platforms in this niche are Palantir and Alteryx, which also happen to be rivals. In this article we shall explore the variance between these two.Palantir
Palantir builds software that connects data, technologies, humans and environments. It has developed several platforms, like Foundry and Gotham that are being used by government bodies and commercial customers as a business solution tool. Generally, its solutions cater to capital markets, crisis response, defense, financial compliance, insider threat, intelligence, and legal intelligence. Palantir Foundry transforms the ways organizations operate by creating a central operating system for their data. Foundry also allows individual users to integrate and analyze the data they need in one place. It allows users to do a better data governance job. It also enables an extensive analysis which cannot be done on a personal computer, or even an on-premises server because of the computational effort that is required. Meanwhile, Palantir Gotham is used primarily by government agencies that look for bad actors hiding in complex networks: terrorist cells, trafficking rings, money laundering schemes, vectors of foodborne illness, and so forth. These organizations use Gotham to bring their data sources and systems together, map the data to a common model, and analyze it in one place. Though Foundry’s market is broad, Gotham is still the best platform on the market for investigative analysis. Apart from sharing the status of a widely used data mining tool, Palantir is also well-known for its controversial uses. Few years ago, the platform was heavily criticized for its role in USA deportation scheme ran by ICE and Britain’s post-Brexit immigration policies.Alteryx
One of the main competitors of Palantir is market space is Alteryx. Alteryx is popular for its provision of an end-to-end data science & analytics platform for enterprises. For instance, its Alteryx APA Platform is known for its ease of use and no-code, low-code analytics that empowers analysts, business leaders, and C-level executives to create and use data-driven insights. Though this product seems tad confusing owing to its complexity, it has a great user interface and this makes it easier to learn. Further, its built-in tool like time Formaters, Filters and Joins facilitate the work of doing data cleansing and data prepping for any ETL job. Even the input and output formats are highly flexible. Also, its functionality of drag and drop makes it the most valuable. Alteryx’s software services cater to industries like financial services, health care, retail, transportation and logistics, oil and gas, pharmaceuticals and biotechnology and more.Market Scenario
According to a survey on a group of over 300 Benzinga investors and traders to determine, whether shares of Palantir or Alteryx stock would grow the most by 2025 – the response has been quite promising for Palantir. 69.2% of survey respondents believed shares of Palantir would grow more in the next five years. In contrast, only 30.8% of respondents said Alteryx will grow the most by 2025. One of the key drawbacks of Alteryx is its high pricing.
There are many data analytics companies that have dominated the industry with their key offerings. Two popular platforms in this niche are Palantir and Alteryx, which also happen to be rivals. In this article we shall explore the variance between these two.Palantir builds software that connects data, technologies, humans and environments. It has developed several platforms, like Foundry and Gotham that are being used by government bodies and commercial customers as a business solution tool. Generally, its solutions cater to capital markets, crisis response, defense, financial compliance, insider threat, intelligence, and legal intelligence. Palantir Foundry transforms the ways organizations operate by creating a central operating system for their data. Foundry also allows individual users to integrate and analyze the data they need in one place. It allows users to do a better data governance job. It also enables an extensive analysis which cannot be done on a personal computer, or even an on-premises server because of the computational effort that is required. Meanwhile, Palantir Gotham is used primarily by government agencies that look for bad actors hiding in complex networks: terrorist cells, trafficking rings, money laundering schemes, vectors of foodborne illness, and so forth. These organizations use Gotham to bring their data sources and systems together, map the data to a common model, and analyze it in one place. Though Foundry’s market is broad, Gotham is still the best platform on the market for investigative analysis. Apart from sharing the status of a widely used data mining tool, Palantir is also well-known for its controversial uses. Few years ago, the platform was heavily criticized for its role in USA deportation scheme ran by ICE and Britain’s post-Brexit immigration chúng tôi of the main competitors of Palantir is market space is Alteryx. Alteryx is popular for its provision of an end-to-end data science & analytics platform for enterprises. For instance, its Alteryx APA Platform is known for its ease of use and no-code, low-code analytics that empowers analysts, business leaders, and C-level executives to create and use data-driven insights. Though this product seems tad confusing owing to its complexity, it has a great user interface and this makes it easier to learn. Further, its built-in tool like time Formaters, Filters and Joins facilitate the work of doing data cleansing and data prepping for any ETL job. Even the input and output formats are highly flexible. Also, its functionality of drag and drop makes it the most valuable. Alteryx’s software services cater to industries like financial services, health care, retail, transportation and logistics, oil and gas, pharmaceuticals and biotechnology and more.According to a survey on a group of over 300 Benzinga investors and traders to determine, whether shares of Palantir or Alteryx stock would grow the most by 2025 – the response has been quite promising for Palantir. 69.2% of survey respondents believed shares of Palantir would grow more in the next five years. In contrast, only 30.8% of respondents said Alteryx will grow the most by 2025. One of the key drawbacks of Alteryx is its high pricing. Sources say that for Alteryx, its stock has been rather volatile over the last year. This volatility was believed to happen due to lower than expected Q2 growth at only 17% and a low forecast for the second half of the year. For a company that has seen 69% compound annual growth for the three years running up to 2023, this was quite a shock to its investors. At the same time, Palantir’s adjusted gross margin, contribution margin (which excludes sales and marketing costs and stock-based compensation), and operating margin witnessed an expansion in the Q4 and also for the full year. In the same quarter (Q4 2023), Palantir had US $5 million or more, including 12 contracts worth US$10 million or more. Some of its major wins included deals with Rio Tinto, PG&E, BP, the FDA, and the NHS. Even the USA Army which already uses Palantir Gotham platform to plan missions, signed a new AI contract , renewed an analytics partnership, and signed a new contract to modernize its ground stations with Palantir over the past year alone. Recently, it secured a huge contract from IBM too. To surmise, both Palantir and Alteryx offer some unique features that make them exception in market and data analytics sector. While choosing between the two and leveraging them for business functions depends on user requirements, budget, etc., purchasing their stock requires a deeper analysis of stock market trends.
Mission to Leverage Decisions from Data
GoodData was founded in 2007 with headquarters in San Francisco and Portland. The company’s mission is to fundamentally change the way businesses use data to make decisions. Many companies have not seen a return on their BI investment, and GoodData believes it is because the insights were not actionable, were not delivered in context or within the workflow. It has asked everyday business users to go out on their own and look at dashboards with no understanding of what to do with the information found on those dashboards. There was good intent behind self-service analytics, but in reality, it was not happening. People were not going to leave their daily workflow to look at a dashboard when that dashboard does not tell them what action to take. The company’s foundation has always been to embedding insights at the point of work and delivering at mass scale.A Passionate Entrepreneur and Insightful Leader
As the Founder and CEO of GoodData, Roman Stanek is a passionate entrepreneur and industry thought leader with over 20 years of high-tech experience. His latest venture, GoodData, was founded in 2007 with the mission to disrupt the business intelligence space and monetize big data. Prior to GoodData, Roman was the Founder and CEO of NetBeans, a leading Java development environment (acquired by Sun Microsystems in 1999) and Systinet, a leading SOA governance platform (acquired by Mercury Interactive, later Hewlett Packard, in 2006).Disruptive Contribution to the Big Data Industry
As businesses have not received the ROI on their BI deployments as expected, GoodData is the leader in educating the public about embedded analytics. Many people don’t understand that embedded analytics is a different animal. GoodData is embedded into the business process and is contextual. The company is not selling technology to IT, instead is selling analytics applications to a business unit for a business problem. GoodData aims to solve domain analytics problems. By being embedded at the point of work, without having to leave the application in which clients are used to working, and because the company is contextual, clients know exactly what to do with the insights that are being presented to them.Innovation and Partnerships Drive Success
Artificial Intelligence and IoT are at the center of today’s innovation. All innovation includes one or both of these technologies and they will continue to grow in importance in the coming years. These technologies will define the competitiveness and success of a business.
GoodData promotes a culture of innovation. The company is continuously investing in the technologies that are disrupting the market and will separate successful businesses from those that are not. As mentioned, Artificial Intelligence and IoT are the cornerstones of today’s innovation and GoodData is fully invested.Awards and Accolades for Excellence
Most recently, GoodData has been recognized as a Leader in the Forrester Wave™, Enterprise BI Platforms with Majority Cloud Deployments, Q3 2023 as well as a Strong Performer in the new Forrester Wave™, Insights Platform-As-A-Service, Q3 2023. Good Data is used by over 50% of the Fortune 500 companies and there are over 1.2 million users on the GoodData platform. And, over 70,000 businesses use GoodData.Challenges and Impediments to Growth
According to Roman, the biggest challenge in the company’s mind is that the industry has been focused on self-service dashboards while the company was focused on embedding insights at the point of work. GoodData was going against the popular trend because it knew that people would not leave their work environment to search for a static dashboard to look at visualizations that were difficult to interpret. It has taken some time for businesses and analysts to catch up to understanding that the only way to get ROI is to provide the insights with context and help guide everyday users in the actions they should take upon being presented with the data.The Future Ahead
The industry is recognizing the value of embedding analytics at the point of work within the user’s workflow, presenting considerable growth opportunities for GoodData in the years ahead. More companies will move away from self-service dashboards to embedding analytics at the point of work. They will also begin implementing machine learning for easily repeatable business processes, allowing frontline workers to spend more time on strategic business decisions.
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