Data Transforming Business

In today's data-driven world, where 90% of business decisions rely on data, harnessing the power of enriched data is paramount for organisational growth. This is where data enrichment for analytics comes in.In this episode of the EM360 Podcast, Head of Content Matt Harris speaks with Andy Bell, VP of Global Data Product Management at Precisely. They discuss and discover how businesses are transforming their strategies by enriching their data with comprehensive demographic, industry, social, and consumer insights, enabling them to make profoundly informed and accurate decisions.Explore how data enrichment revolutionises various sectors:Retail: Craft highly targeted marketing messages using precise customer profiling, identify lucrative markets, and pinpoint expansion opportunities.Insurance: Enhance policy pricing decisions with a deep understanding of a property’s proximity to diverse risk factors, ensuring more informed and competitive offerings.Telco: Optimize network planning and infras

Fivetran automates data movement out of, into and across cloud data platforms. It automates the most time-consuming parts of the ELT process from extracts to schema drift handling to transformations, so data engineers can focus on higher-impact projects with total pipeline peace of mind. With 99.9% uptime and self-healing pipelines, Fivetran enables hundreds of leading brands across the globe, including Autodesk, Condé Nast, JetBlue, Lufthansa, Morgan Stanley and Pitney Bowes, to accelerate data-driven decisions and drive business growth. In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Fivetran’s Founder and COO Taylor Brown at Big Data LDN to discuss:The data space and how Fivetran fits inHow customers are reacting to generative AI and MLTrends set to shake up the industry in 2024 and beyond

Data productization. The art of turning raw data into business-ready consumable data products. Applying product management principles to data management, data productization can connect your business objectives to data and stay ahead of the curve. But what things should you consider when building a data product? What challenges are likely to arise? And how can you effectively bridge the gap between data teams and business units to ensure the successful adoption and utilization of these products by end users?In this episode of the EM360 Podcast, Analyst Kate Strachnyi speaks to Colin Brown, CMO at Revelate and Nicolas Doyen, CPO at Revelate, to discuss:Building a data productEnsuring successful adoption by end usersTechnologies shaping the future of data productization

What is the relationship between product content and customer experience?A symbiotic one, say experts, but what technologies need to be implemented and how can companies bring in new tools to eliminate their digital debt?In this episode of the EM360 Podcast, Analyst George Firican speaks to Derek Corrick, GM of Data at Pivotree and Justin Anovick, Chief Product Officer at Syndigo, to discuss:The relationship between product content and CXLeveraging AI/ML and how that impacts clientsBest practices for solid content strategy

Corporate Performance Management (CPM) is a set of processes, methodologies, and tools used by organisations to measure and manage their performance and achieve their strategic objectives. CPM encompasses various activities that help businesses plan, monitor, and analyze their performance against key performance indicators (KPIs) and targets.But why is it so important? How does this technology interact with other business functions? And how can companies get started?In this episode of the EM360 Podcast, Analyst Doug Laney speaks to Arthur Forbus, Managing Director and COO at HollandParker, to discuss:CPM and why every company needs itMisconceptions around CPMHow to raise your CPM game

Is the modern data stack dead? How can you better leverage your MDS? And how can you stay ahead of the curve in a market which is seeing more and more new trends emerging constantly?These were questions posed at the recent Modern Data Stack Roadshow; Fivetran's follow-up to the successful Modern Data Stack Conference. These half-day events convene top industry experts to discuss how to drive impact and business growth using data.With plenty of exciting talking points raised by the industry leaders in attendance, how are some of the biggest movers and shakers talking about the data space right now?In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Mark Van De Wiel, Field CTO at Fivetran, to explore: Keeping up with the modern data stackLeveraging your modern data stackAdvice on tackling complex data challenges

External data integration is crucial for organisations seeking to enhance their understanding of customers, markets, and industry trends.By leveraging data from external sources, businesses can gain valuable insights, make informed decisions, and identify new opportunities. But what challenges arise when implementing external data integration, and how can companies navigate some of the common pitfalls?In this episode of the EM360 Podcast, Wayne Eckerson speaks to Dan Lynn, SVP of Product at CRUX, about:External data integration and its advantagesAddressing challengesBest practices and avoiding common mistakes

Moving from an on-prem infrastructure to a frictionless cloud model has become a key goal for many companies. From scalability to improved security, as well as cost-saving benefits, moving to the cloud bring a lot of benefits. But what challenges are enterprises facing in their migration, and how can this process be made easier?In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Alex Merced, Developer Advocate at Dremio, to discuss:On-prem data lakes Moving to a frictionless cloudHow to streamline the migration process

Data pipeline automation is revolutionizing the way organisations handle data. This new approach to data management is challenging the traditional modern data stack, which relied on a series of disparate tools to handle different aspects of data processing. With data pipeline automation, organizations can simplify their data stack, relying on a single tool to manage the entire process. This shift will allow businesses to focus on insights and decision-making, rather than spending time wrangling data. As a result, data pipeline automation will become the key component of the post-modern data stack.In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Sean Knapp, Founder and CEO at Ascend.io, and we’re here to talk about:Solving data stack challengesAutomation in data pipelinesWhat the ultimate solution will be

Frictionless commerce is the ability to seamlessly find customers, establish trust, and transact and deliver products without any hiccups.However, enterprises face three significant problems in achieving frictionless commerce: getting the right data, managing tech debt, and ensuring data interoperability. And much like the old children's book "I Know an Old Lady Who Swallowed a Fly" - each problem seems to lead to another.That's where Data-as-a-Service (DaaS) comes in. A cloud-based service that provides users with on-demand access to high-quality data, it can help organisations with these challenges by providing them with accurate and reliable data while reducing the burden of managing and maintaining it.In this episode of the EM360 Podcast, Analyst Doug Laney speaks to Derek Corrick, General Manager of Data Management at Pivotree, to discuss:Frictionless commerce and how it can be acceleratedCommon challenges in data management Data-as-a-Service and how to get started

Data management is essential for retailers to manage their data effectively to gain valuable insights into customer behavior, preferences, and purchase patterns. By doing so, retailers can make data-driven decisions and improve their operations, sales, and marketing strategies.However, managing data can be challenging for retailers due to the volume, variety, and velocity of data generated by multiple sources, such as social media, mobile devices, and online platforms. Retailers must also comply with data privacy regulations and ensure the security of their customers' personal information. Additionally, they need to invest in advanced technology and skilled personnel to manage data effectively.In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Ramesh Shurma, Founder and CEO at Orion Governance, to discuss:Major data challenges faced by retailersProtecting data assets in the face of recessionGovernance predictions for the next five years

In traditional data architecture, data was always centralised in a data warehouse or a data lake and governed by a centralised team. However, with the rise of distributed systems, microservices, and agile methodologies, this approach has proven to be inadequate for managing data at scale. Data Mesh proposes a different approach, where data is treated as a product and owned by the teams that produce it. In other words, it's a way of thinking about data management that focuses on decentralisation and autonomy. But how can companies use this to their advantage?In this episode of the EM360 Podcast, Analyst Christina Stathopoulos spoke to Paolo Platter, Co-Founder and CTO at Agile Lab, about: Successful data mesh strategiesBenefits vs monolithic data lakesCustomer success storiesAgile Lab works with an array of clients across the globe, creating business vertical solutions to address specific challenges and needs in their field of activity. To hear about their succ

Location intelligence. Location intelligence is crucial for a company's data-driven decision-making process, providing insights into the relationship between location and business operations. It helps identify new market opportunities, optimize operations, improve customer experiences, mitigate risks, and provide a competitive advantage.By analyzing location-specific information, companies can make informed decisions that drive growth, reduce costs, and increase profitability. Ultimately, location intelligence is a valuable tool for companies seeking to make strategic decisions that optimize operations, enable growth, and gain a competitive edge in their respective industries.In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Adam Ejsmont, Co-Founder of Echo Analytics, about:Location intelligence in the modern worldData collection and ensuring data privacyWhy investing in location intelligence is critical

Data is the backbone of any successful business, and having a 360-degree view of it is crucial to understand the key metrics and drivers of the organization. By collecting, processing, and analyzing data from various sources such as customer interactions, financial transactions, and employee performance, your business can gain valuable insights into its operations. This 360-degree view of the business data will allow your company to take a data-driven approach to decision-making, leading to better results and improved performance.In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Dan Everett, VP of Product and Solution Marketing at Informatica about:Connecting different types of data Collecting, analysing and storing data while complying with regulationsBusiness-wide observability challenges

Data observability refers to the ability to collect, measure, and analyse data from various sources in order to understand the current state and behaviour of a system.This includes monitoring the system's performance, availability, and errors, as well as identifying patterns and anomalies in the data. By implementing data observability, organisations can gain insights into their systems and make data-driven decisions to improve performance, optimize resources, and reduce costs. Common tools used for data observability include logging, metrics, tracing, and alerting. In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Lior Gavish, Co-Founder and CTO at Monte Carlo, to discuss:Getting started with data observabilityObservability trends for 2023How to implement and common challenges

Predictive data intelligence is the use of data, AI-driven algorithms, and machine learning techniques to quickly connect data consumers with the most relevant data they need to drive their business initiatives and deliver greater value.The goal of predictive analytics is to go beyond simply describing data to enable data consumers to accelerate the next-best actions to take for more effective decision making. For example, a retailer can understand their most relevant and high-quality data sets to better forecast consumer demand for a product, or a financial institution may identify the most accurate, complete customer data used to fuel analytics that help identify the likelihood of default on a loan.In this episode of the EM360 Podcast, Analyst John Santaferraro speaks to Informatica’s Ian Stahl, Senior Director of Product Management and Chris Phillips, VP of Product Management to discuss:Shifting from business intelligence to predictive data intelligenceData sharing and data marketp

Data engineering is how companies design and build systems for collecting and using their data at scale. A critical practice as companies are pressured to make more and more data-driven decisions, data engineering is essential for enterprises to get ahead.  In this episode of the EM360 Podcast, Editor https://em360tech.com/user/3673 (Matt Harris) speaks to https://www.linkedin.com/in/salma-bakouk-2999711b6?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAADJVC1UBRDqdneOVftZFsyUXKwa2JZVptAE&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3Bzi1fFov0SOWW2R4dOI1ocw%3D%3D (Salma Bakouk), Co-Founder and CEO at https://em360tech.com/solution-providers/sifflet (Sifflet), to discuss; Trends shaping the data engineering industry Caring about data reliability and observability What the future brings

Data management is essential for the enterprise to get right, especially now as firms across all sectors are collecting and using vast amounts of data.  But what exactly is good data management? Why do we need it? And what are some of the unacknowledged ramifications that have serious impacts on our day-to-day lives? In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3642 (Doug Laney) speaks to https://www.linkedin.com/in/mkapushesky/ (Misha Kapushesky), CEO at https://em360tech.com/solution-providers/genestack (Genestack) and https://www.linkedin.com/in/vivek-iyer-686b301/ (Vivek Iyer), Team Lead, Human Genetics Informatics, from the https://www.linkedin.com/company/wellcome--institute/ (Wellcome Institute), to discuss: What makes good data management How data impacts everyday life Driving behavioural and cultural change

Data culture is becoming an increasingly important philosophy in the modern enterprise. Making data-driven decisions is critical to the success of a company in today’s world, and there really is no better way to do that than ensuring a data culture runs through the firm. There are plenty of studies that show a correlation between the maturity of a data culture and the success of a business, including this one from Collibra which states “Organisations with higher levels of maturity across their data culture are likely to realise higher business benefits and performance versus peers.” In this episode of the EM360 Podcast, Editor Matt Harris spoke to Databricks’ Field CTO Robin Sutara at Big Data London 2022 to discuss: Building and maintaining a data culture Data culture maturity The Women in Data movement

As data continues becoming a core part of how businesses operate and make decisions, managing data quality has never been so important.  Poor data quality can hit all enterprise levels hard, from marketers annoying prospects to supply chains becoming unable to automate processes properly. In this second episode of the three-part EM360 Podcast series with Anomalo on data quality, https://www.linkedin.com/in/eshmu/ (Elliot Shmukler), Co-Founder and CEO at https://em360tech.com/solution-providers/anomalo (Anomalo) joins Analyst https://em360tech.com/user/3633 (Christina Stathopoulos) to discuss: The right time for data quality monitoring What happens if you wait too long Who should be involved