BI Modernization Basics: What is BI Modernization & Why Is It Important?
Data is, unquestionably, one of the most critical assets a modern global organization can have. In today’s intensely competitive business landscape, quality data can mean the difference between becoming a thriving industry leader or languishing in the lower market rankings. But, simply collecting and storing data for occasional analysis is not enough: successfully managing that data and continually deriving insights from it brings the true value of business [...]
Finding the Right BI Solution: 4 Considerations When Evaluating Your Options
Business intelligence (BI), if done right, can have a significantly positive impact on your organization. BI can enable faster decision-making and improved collaboration across teams; it can uncover insights about your customers, current processes, and how to work more efficiently. It can also help you save valuable budget dollars or even reveal new ways to make your businesses more profitable — not to mention improve your employees’ productivity, [...]
5 Common Challenges to MLOps Capabilities & Development
Enterprise interest in artificial intelligence and machine learning (AI / ML) is exploding with experts forecasting a 10x increase in spending over the next five years. However, the complex nature and exacting demands of effective AI / ML are above and beyond those experienced with traditional, legacy systems. As a result, a new discipline, MLOps, is emerging to manage these capabilities and tackle challenges. [...]
How to Develop Your BI Modernization Roadmap
As data creation zooms ahead at the speed of light, nothing is more detrimental to data-reliant businesses than ineffective, burdensome legacy infrastructure. Outdated tech can stand in the way of businesses adopting cloud-based apps, managing big data, delivering the right sight to the right person, and leveraging cloud warehouses for data storage. In short, when data isn’t being used effectively, businesses get left behind. [...]
6 Crucial Considerations for MLOps Success
Interest in AI / ML is exploding, but these new techniques and technologies present some unique challenges that can result in suboptimal results if not addressed correctly. Dysfunctional AI / ML efforts can be characterized by high costs, an inability to scale, and slow or unnecessarily limited outcomes — but it doesn’t have to be that way. Are your machine learning efforts proving [...]
What “Mad Men” Can Teach Us About the Customer Experience and How ML / AI Capabilities Are Improving It
The first episode of “Mad Men” features a focus group in a brightly lit room. Chairs are placed neatly in rows along laboratory-grade clean counters. Along these countertops lie small shiny cylinders, each with individual tags and a box of tissues to accompany them. Amongst these chairs enter a line of secretaries, each assigned to a seat.
5 Pillars of Data Observability: How Recency, Distribution, Volume, Schema, and Lineage Maintain Healthy Data
For data observability, those guiding principles can be simplified into five pillars: recency, distribution, volume, schema, and lineage. Evaluated together, they help organizations guarantee the health of their data.
Data Observability in Action: How Maven Wave Helped Assess an Unhealthy Data Flow for an Enterprise
As you read this, hundreds of thousands of megabytes of new data have already been generated — and that’s a conservative calculation.
What Is Data Observability? Does It Live Up to the Hype?
Data, data, and more data: In today’s landscape, data is driving critical decisions and is considered the lifeblood of an organization. With an increasingly digital economy, more and more enterprises are making key financial and customer decisions based on data input...
Modernizing Your SAP S/4HANA Analytics
When Home Depot wanted real-time analytics from its SAP data to manage inventory, the company turned to cloud-based analytics to avoid stockouts and increase sales. Like many SAP users, the home improvement retailer relies on the power of SAP S/4HANA to create an intelligent enterprise and drive digital transformation.
Data Science Terminology 101: 31 Must-Know Definitions
Have you ever searched for something only to be bombarded later with a plethora of ads for related services or products? Or crazier still, have you mentioned a product name aloud and been greeted with an ad for that same service a few hours later?
The Five W’s of Spatial Data Science and Spatial Data Analytics
Spatial Data Science is a term we use frequently at Maven Wave to describe the use of spatial data, algorithms, and analytical methods applied in concert with more traditional machine learning and deep learning techniques.
4 Top Challenges to Implementing Data Science Modernization
The emergence and growing capabilities of the public cloud have led to a revolution in new products, processes, and tools. Lower costs have supported an explosion in data, and new analytical capabilities have created an exponential increase in insights — just to name a few benefits.
The Case for Data Science Modernization: 6 Shortcomings of Legacy Solutions
In a recent white paper, The Inevitability of Data Science Modernization During the Machine Learning and AI Revolution, Maven Wave detailed how recent developments in data science modernization (DSM) are setting the foundation to support the transformative power of artificial intelligence (AI) and machine learning (ML).
The Inevitability of Data Science Modernization During the Machine Learning and AI Revolution
In the business world, machine learning (ML) and artificial intelligence (AI) are keys to the future of modern enterprises. A recent survey from ESIThoughtLab found that two-thirds of business leaders see AI as critically important for their future.
Taking Data Analytics to New Heights with Visual BI
Atos and Maven Wave see data and cloud as the core pillars of digital transformation. You’ve probably heard (or read) us say that modern enterprises can’t compete without data-driven, cloud-based practices.
Unlocking the Future of Healthcare with Google Cloud’s Healthcare Data Engine
Healthcare and life sciences organizations (HCLS) were moving to the cloud even before government mandates for interoperability came into play. Forward-thinking providers, insurance companies, and drug companies have been using the power of cloud to redefine the patient experience, unearth the value of data, and improve the delivery of care for years.
The Raw Reality of Data Analytics and Cloud Migration with Brad Foster
On a recent episode of the Data Movers Podcast, our very own Brad Foster sat down with JSA CEO Jaymie Scotto Cutaia and a top B2B influencer in the tech, telecom, and data center space, Evan Kistel.
Enabling the Data Analyst: Google Cloud Welcomes Dataform
Google Cloud recently announced its acquisition of Dataform, a platform that empowers analysts to manage the entire flow of data within the warehouse, using a single, unified workflow. Incredibly powerful, Dataform is the tool used for transformation of data, reshaping, cleaning, and crunching. Since Dataform is now part of Google Cloud, it is available for free. Google is offering a product that can truly change the way that all [...]
Webinar Series: Navigating the Cloud Data Journey
Data and reporting play a key role in informing business strategy nowadays, but building a robust data program is harder than it sounds. Should you migrate your data to the cloud little-by-little or all at once? If you’ve already migrated, how do you ensure cost control and optimization? And once you have the basics down, how can you dive deeper into advanced analytics programs?
Google Cloud Next ‘20: OnAir and in the Cloud with Maven Wave – Data Analytics Week
Across screens worldwide, Google Next ‘20: OnAir attendees are taking a deeper dive into today’s most commanding cloud topics. Led by Google Cloud experts and featured guests, the all-digital event is helping leaders solve some of their most crucial challenges with fresh on-demand content, interactive experiences, and more. The nine-week event is halfway through, but the content is available on-demand by building a customizable playlist. [...]
5 Critical Components for Assessing the Quality of Enterprise Data
One of the most vital business lessons to derive from the ongoing global pandemic is the importance of data quality. While making key decisions around the best ways to rapidly implement and pivot strategies, ensuring you have high-quality data is essential. During this crisis, those who do not have the necessary data needed to steer these critical choices properly have been struggling to put a plan in place. [...]
How Data Enables the “Smart” in Smart Factories
The next generation of manufacturing is here. It’s no secret that manufacturers must continue to prove their relevance by leveraging emerging technology trends to stay on pace with modern-day customer demands and achieve autonomous operations. When building an innovative smart factory, there is no one-size-fits-all. Still, the groundwork is the same - connecting data, machines, people, and processes to deliver the next generation of manufacturing. [...]
Will Your Business Live By Data, or Die By Data?
The global COVID-19 pandemic is teaching the world a few key lessons about the importance of data quality. Good data, with standard definitions, timeliness, reliable curation, and ease of access can drive policy, priorities, informed risk-taking, and decisions. Good data allows an agile organization to execute a plan in response to a briskly changing environment. Bad data drives ambiguity, confusion, chaos, and loss. Bad data is a fog [...]
Celebrating 10 Years of Google Cloud’s BigQuery: A Look Back
Congratulations BigQuery on celebrating 10 years! As an early entrant to the Google Cloud Partner ecosystem, we at Maven Wave have enjoyed seeing the platform grow and evolve from beta to the industry leader it is today. Let’s take a look back at the evolution of BigQuery over the past 10 years. During the beta stage, though the product [...]
Powering Enterprise AI Projects with BigQuery
Google Cloud’s BigQuery has come a long way since it launched in 2010, and even since machine learning (ML) was first added to the serverless, scalable cloud data warehouse last year. Google CEO Sundar Pichai publicly introduced the company’s Artificial Intelligence (AI) - first strategy in 2017 and focused on “making AI ‘simple, fast and useful’ for enterprises” in the months following, according to CMSWire. [...]
3 Ways Retailers Can Personalize Customer Experience Using Technology
The modern consumer expects personalization as a standard of service. And even more, they expect to have a seamless transition between their online shopping experience and in-store interactions. Today, with much focus on the omni-channel experience, recognizing customers on a personal level still garners results, but it requires a new twist: using technology to augment and improve the shopping experience wherever and whenever the customer chooses to engage. [...]
7 Steps for Successfully Building a Human-in-the-Loop Machine Learning Model
Even though human-in-the-loop is still in its “early innings,” companies can generate considerable business value in the near-term by implementing this emerging technology. At most workplaces, it’s now expected that employees across a wide array of functions are able to automate their routine daily tasks through the use of predictive analytics. This by no means insinuates employers want their staff to automate themselves out of a job; rather, [...]
A Guide to Google BigQuery Inner Workings
For many years now, businesses have utilized databases for analytical workloads. As time has gone by, the need for quick and accurate insights into all aspects of the business have increased as companies look to harness data to gain a competitive advantage. Traditional databases where compute and storage are tightly tied together have been expensive and inefficient. Newer Cloud Native databases, such as Google Cloud's BigQuery, take advantage [...]
Top 3 Rules For Deploying AI Across The Enterprise
Consider how far we’ve come with artificial intelligence (AI) and machine learning (ML) in such a short time. Three years ago, AI and ML were new to everyone; data scientists were the only ones who understood the technology and could envision the applications. Plus, the only businesses that could afford to even consider it were large organizations such as the U.S. Department of Defense, NASA, and major universities. [...]
Why Enterprises Are Playing Catch-Up with AI and 5 Tips for Diving In
Artificial intelligence (AI) has completely transformed in the last five years due to the increased availability of computing resources in addition to a better understanding of techniques and customer demand. In fact, the adoption of machine learning (ML) and AI is mirrored by the general adoption of cloud strategy. A recent Gartner CIO Survey showed a rise in AI implementation of 270 percent over the last four years, VentureBeat [...]
Machine Learning at a Glance: Highlights from Google Cloud Research
The majority of today’s businesses are investing in ML, according to our research. Use cases vary widely by industry, but several key applications — including process automation and customer behavior analysis — are common. ML adopters are seeing an especially high degree of impact from predictive analytics, a category of techniques that use data to assess the likelihood of future outcomes and help businesses solve complex problems. [...]
Machine Learning Now Available in Google BigQuery
One of Google Cloud Platform’s most popular products, BigQuery, recently announced the addition of some exciting new functionality: the ability to create and execute machine learning (ML) models directly inside of the platform. BigQuery has become incredibly popular because it enables interactive analysis of large datasets, making it easy for businesses to share meaningful insights and develop solutions with analytics. However, often times users of BigQuery aren’t using [...]
CAO Fall Recap Take 2: How To Successfully Implement Machine Learning
In a previous post, we shared the recurring question from the first day of the Chief Analytics Officer fall conference: how can you best apply insights from your data? In response to that question, several presentations offered guidelines for building machine learning models and shared case studies showing how companies are currently utilizing these solutions. During the remainder of the conference, while many speakers focused on different aspects [...]
Transforming Marketing Through Analytics
In a previous blog post, we explored the rapid growth of marketing technology applications and the corresponding explosion of marketing data. Marketing teams today have a proliferation of data silos supporting a diverse portfolio of marketing technologies. It’s not unusual for an enterprise to be using twenty or more best-of-breed apps for marketing in addition to enterprise applications like ERP, customer relationship management, and workforce management. [...]
Building a Holistic Customer View from Your MarTech Apps
Today’s marketers have an awe-inspiring, some might say overwhelming, range of responsibilities. What was once a narrow focus on advertising and promotion has expanded to include a wide range of content creation and distribution, customer relationships, social media, and customers’ experiences throughout their lifecycle both on- and offline. At the same time, many businesses have become data-driven, holding all executives accountable for progress against key metrics. [...]
From Science to Delivery: Making the Most of Machine Learning with DevOps Principles
Machine learning is garnering a great deal of attention and resources right now but experience is showing that the journey from promising experiments to functioning solutions is not always an easy one. In order to avoid having pilots being no more than one-off science experiments it takes special care and effort. One way to deal with this problem is to adopt the principles of DevOps as useful guideposts [...]
4 Unexpected Uses of Machine Learning
The pace of technology is continually accelerating and we are seeing more and more machine learning solutions being utilized across industries and even in our personal lives. But beyond the practical application of the technology, data scientists are developing some truly amazing use cases for how ML can enhance our lives unexpected ways. From identifying which shop your ramen noodles came from to saving the rainforests, the possibilities [...]
Smarter Marketing Decisions with Analytics and Google Cloud
On a daily basis, marketers are tasked with identifying new ways to target customers through campaigns, emails, events, ads, social media, and more. But, how do you know if your marketing strategy is effective and making an impact on sales? This is where marketing analytics can make a huge difference; it’s crucial for companies to understand the value of marketing efforts. [...]
4 Simple Ways AI is Changing Business
We’ve all benefited from artificial intelligence (AI) enhancing our personal lives; from using GPS to predict the fastest route to having Spotify suggest songs that we may like. Artificial intelligence is not just affecting our personal lives, but we are now seeing it being adopted by the enterprise. In the coming years, we can expect AI to become one [...]
Reinvigorate Your Data Analytics Team with Serverless Computing
What is serverless computing? The funny thing about “serverless computing” is that in reality, it still requires servers. The name is actually used because the server management and capacity planning decisions are completely hidden from the developer or operator. Sometimes referred to as “Function-as-a-Service” (FaaS), serverless computing is the concept of executing your application code as a series of tasks in an environment completely managed for you. Pricing [...]
Ask the Expert: Machine Learning
In the era of digital transformation, businesses are reporting machine learning (ML) their top business priority. Companies are rapidly beginning to rely on ML to streamline their processes, ultimately increasing efficiencies. While ML is being implemented across many industries, it's only the start of this journey. In this Ask the Expert, we dive deeper in topics about ML with our expert, Sumeet Singh. [...]
How to Leverage Geolocation Data In Any Industry
No matter what industry you work in today, all businesses are collecting enormous amounts of customer data. Most likely, a lot of that data has a geolocation component to it. Some of the use cases for taking advantage of that data may be obvious (i.e.mobile ordering), but there are many other ways to monetize and discover value from these analytics. Below we provide three unique use cases for [...]
How to Successfully Run Machine Learning with Google Cloud Platform
6 Essential Components If you’re reading this article, you are likely already using Google Cloud Platform (GCP), planning to use it, or maybe you are simply intrigued to learn more. Irrespective of your situation, there are some common patterns and approaches to running Machine Learning (ML) with GCP. Below are the top 6 essential components for a successful outcome. [...]
Top 5 Takeaways from the CAO Forum
Maven Wave sponsored the 2017 Chief Analytics Officer Forum in Boston on October 3-5, 2017, hosted by Corinium Global Intelligence. The conference is led by CAO’s and attended by 300+ top-level analytics executives. It was a well-executed event with insightful speakers, peer-to-peer networking, and valuable actions for analytics teams from all industries and sizes. Below are our top takeaways and insights from the conference. [...]
Beyond the Machine Learning Hype: Solving Vexing Problems in New Ways
Gartner’s latest quarterly IT spending forecast delivers big news about the cloud’s role in global IT expenditures. The firm expects worldwide IT spending to reach $3.8 trillion this year, rising 3.2% over 2018, as the company points out here. A major driver of this growth is the enterprise software segment, which is projected to increase 8.5% this year and another 8.2% in 2020 – reaching $466 billion that [...]
Tapping IoT to Improve Marketing, Logistics, and Data
The Internet of Things (IoT) has made a huge impact across many industries in recent years. The ability to collect real-time analytics from dispersed machines and devices has opened up a whole new world of opportunity. IoT is a connection of devices that capture data; this collection of data allows organizations to increase efficiency and productivity through the assessment of IoT analytics, which in turn, cuts costs for [...]
Ask The Expert: Data Analytics
In today’s market, data analytics play a large role in the success of an organization. Analyzing data leads organizations to uncover insights to make more intuitive business decisions. In the age of digital transformation, utilizing analytics within your business is a necessity to stay competitive. In this Ask the Expert interview, we sat down with our newly hired data analytics expert, Todd Truesdell, to answer frequently asked questions [...]
Machine Learning: The New Proving Ground for Competitive Advantage
A recent survey conducted by MIT Technology Review Custom and Google Cloud reveals that while the majority of businesses are struggling to apply machine learning, others are hard at work developing strategies for the technology — and are already realizing genuine ROI. Get the latest industry news and insights delivered straight to your inbox. Sign up for our Newsletter [...]