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In this episode Paul Blankley and Ryan Janssen explore the power of natural language driven data exploration combined with semantic modeling that enables an intuitive way for everyone in the business to access the data that they need to succeed in their work. Businessintelligence is a crowded market.
Summary Businessintelligence has gone through many generational shifts, but each generation has largely maintained the same workflow. Data analysts create reports that are used by the business to understand and direct the business, but the process is very labor and time intensive.
Disclaimer: Throughout this post, I discuss a variety of complex technologies but avoid trying to explain how these technologies work. The goal of this post is to understand how data integrity best practices have been embraced time and time again, no matter the technology underpinning.
Summary Businessintelligence has grown beyond its initial manifestation as dashboards and reports. In its current incarnation it has become a ubiquitous need for analytics and opportunities to answer questions with data. What is your view on the role of businessintelligence in a data driven organization?
Summary Businessintelligence is often equated with a collection of dashboards that show various charts and graphs representing data for an organization. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm.
Summary Businessintelligence efforts are only as useful as the outcomes that they inform. Rob shares some useful insights gained through his consulting work, and why he considers Power BI to be the best option on the market today for business analytics. If you hand a book to a new data engineer, what wisdom would you add to it?
In this episode Amnon Drori, CEO and co-founder of Octopai, discusses the business problems he witnessed that led him to starting the company, how their systems are able to provide valuable tools and insights, and the direction that their product will be taking in the future. What is OctopAI and what was your motivation for founding it?
Summary Businessintelligence is the foremost application of data in organizations of all sizes. Zing Data is building a mobile native platform for businessintelligence. Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines.
Summary BusinessIntelligence software is often cumbersome and requires specialized knowledge of the tools and data to be able to ask and answer questions about the state of the organization. The current goal for most companies is to be “data driven” How would you define that concept?
Summary Businessintelligence is a necessity for any organization that wants to be able to make informed decisions based on the data that they collect. Unfortunately, it is common for different portions of the business to build their reports with different assumptions, leading to conflicting views and poor choices.
The best part to jump on the bandwagon of information technology or IT is, there is an enormous possibility for an individual if he or she starts studying for a diploma or a degree, does either a master's degree or a research course. He or she can get a full-fledged engineering degree. You can learn CCNA, CCNP and more from CISCO academy.
In this episode Crux CTO Mark Etherington discusses the different costs involved in managing external data, how to think about the total return on investment for your data, and how the Crux platform is architected to reduce the toil involved in managing third party data. When is Crux the wrong choice?
Summary With the proliferation of data sources to give a more comprehensive view of the information critical to your business it is even more important to have a canonical view of the entities that you care about. Can you start by establishing a definition of data mastering that we can work from?
Summary The core mission of data engineers is to provide the business with a way to ask and answer questions of their data. This often takes the form of businessintelligence dashboards, machine learning models, or APIs on top of a cleaned and curated data set. What is the story behind the name?
Experience the power of BusinessIntelligence, a tech-driven methodology to gather, analyze, and present businessdata. This process helps showcase data in a user-friendly way with the help of reports, charts, or graphs. You will get flooded with options If you look for businessintelligence analyst jobs near you.
Internally, banks are using AI to reduce the burden of datamanagement, including data lineage and data quality controls, or drive efficiencies with businessintelligence particularly in call centers. Those requirements can be fulfilled by leveraging cloud infrastructure and services.
Summary This podcast started almost exactly six years ago, and the technology landscape was much different than it is now. In that time there have been a number of generational shifts in how data engineering is done. Parting Question From your perspective, what is the biggest gap in the tooling or technology for datamanagement today?
Today’s business world is very complex and always changing, so businesses have to be able to respond quickly to changes in technology, consumer behaviour, and market conditions. The huge amount of data created every second is one of the main reasons for this complexity. How to Pick the Right BI Platform?
The Omni Platform expands the analytics capabilities of the AI Data Cloud and allows customers to extract more value from their data, faster. Omni combines the flexibility and speed of modern businessintelligence (BI) and embedded analytics with the governance and consistency of traditional data modeling tools.
BusinessIntelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.
The strategic, tactical, and operational business decisions of a company are directly impacted by Businessintelligence. BI encourages using historical data to promote fact-based decision-making instead of assumptions and intuition. What is BusinessIntelligence (BI)?
The key has the right tools, starting with knowing what data is important for your business. Businessintelligence (BI) and business analytics (BA) are two terms that are often used interchangeably, but there is some important difference between businessintelligence and business analytics.
The work of businessintelligence analysts holds the key to such a solution. These experts are essential in today's data-driven world for assisting businesses in making wise decisions and remaining competitive. Who is a Businessintelligence Analyst and what do they do?
In this episode Abe Gong brings his experiences with the Great Expectations project and community to discuss the technical and organizational considerations involved in implementing these constraints to your data workflows. Can you describe what your conception of a data contract is? Closing Announcements Thank you for listening!
It’s not always the most accurate indicator, but a quick glance at google trends sees Data Engineer rocketing in popularity, compared to more traditional functions such as BI and ETL Developer: google trends Now, that’s not saying that the other roles are going away, not by a long stretch.
Summary The modern data stack has made it more economical to use enterprise grade technologies to power analytics at organizations of every scale. Unfortunately it has also introduced new overhead to manage the full experience as a single workflow. Your flagship (only?) product is a platform that you're calling DataOS.
In this episode she shares the strategic and tactical elements of how to make more effective use of the technical and organizational resources that are available to you for getting work done with data. Trusted by the data teams at Fox, JetBlue, and PagerDuty, Monte Carlo solves the costly problem of broken data pipelines.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagementData and analytics leaders, 2023 is your year to sharpen your leadership skills, refine your strategies and lead with purpose. Can you describe what the SQLake product is and the story behind it?
Summary The majority of analytics platforms are focused on use internal to an organization by business stakeholders. As the availability of data increases and overall literacy in how to interpret it and take action improves there is a growing need to bring businessintelligence use cases to a broader audience.
Summary Data pipelines are the core of every data product, ML model, and businessintelligence dashboard. The folks at Rivery distilled the seven principles of modern data pipelines that will help you stay out of trouble and be productive with your data. Closing Announcements Thank you for listening!
Data Aggregation Data aggregation is a powerful technique that involves compiling data from various sources to provide a comprehensive view. This process is crucial for generating summary statistics, such as averages, sums, and counts, which are essential for businessintelligence and analytics.
Summary Building data products is an undertaking that has historically required substantial investments of time and talent. With the rise in cloud platforms and self-serve datatechnologies the barrier of entry is dropping. For organizations that have an existing data team, how does the platform augment/simplify their work?
The team at Immuta has built a platform that aims to tackle that problem in a flexible and maintainable fashion so that data teams can easily integrate authorization, data masking, and privacy enhancing technologies into their data infrastructure. If you hand a book to a new data engineer, what wisdom would you add to it?
Summary The market for businessintelligence has been going through an evolutionary shift in recent years. Lightdash has fully embraced that shift by building an entire open source businessintelligence framework that is powered by dbt models. Can you describe what Lightdash is and the story behind it?
The toughest challenges in businessintelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big datatechnologies like Hadoop have become a complement to various conventional BI products and services.
Summary The reason for collecting, cleaning, and organizing data is to make it usable by the organization. One of the most common and widely used methods of access is through a businessintelligence dashboard. Superset is becoming part of the reference architecture for a modern data stack.
They also discuss the current state of the market for these technological patterns and how to take advantage of them in your own work. In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
Progress is frequent and continuous, especially in the realm of technology. The advent of one technology leads to another, which sparks another breakthrough, and another. A data warehouse enables advanced analytics, reporting, and businessintelligence. Today, the cloud has revolutionized the potential for data.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. What are your goals with this book?
The market for analytics is flourishing, as is the usage of the phrase Data Science. Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization.
My guest this week is Kulani Likotsi , the Head of DataManagement and Data Governance at one of the four biggest banks in Africa. She’s had a rising career journey going from an analyst, to a BusinessIntelligence developer, to the data warehouse team, to the data governance team.
Over the years, the technology landscape for datamanagement has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Use cases change, needs change, technology changes – and therefore data infrastructure should be able to scale and evolve with change.
In this episode Isaac Brodsky explains how the Unfolded platform is architected, their experience joining the team at Foursquare, and how you can start using it for analyzing your spatial data today. What are some of the core challenges of working with spatial data? When is Unfolded the wrong choice?
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