Don't Panic! It's Just Data

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?

• Keeping up with the modern data stack
• Leveraging your modern data stack
• Advice 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?

• External data integration and its advantages
• Addressing challenges
• Best 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?

• On-prem data lakes 
• Moving to a frictionless cloud
• How 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 challenges
• Automation in data pipelines
• What 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 accelerated
• Common 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 retailers
• Protecting data assets in the face of recession
• Governance 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 strategies
• Benefits vs monolithic data lakes
• Customer success stories

Agile 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 success stories and the ways in which they exceed their clients' expectations, skip to 19:40.

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 world
• Data collection and ensuring data privacy
• Why 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 regulations
• Business-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. 

• Getting started with data observability
• Observability trends for 2023
• How to implement and common challenges