Summary Raiko Limmart, CEO and co-founder of LiTech (https://LiTech.app for a prolonged demo, mention Uncle Data!), discusses the importance of data observability and its challenges. He shares his journey into data quality assurance and explains the components of data observability, including data validation, profiling, and cataloguing. Raiko highlights the need for companies to start early with data observability and offers insights into LiTech's services, which automate data validation, detect anomalies, and provide insights on data quality. He also discusses the role of machine learning and AI in data observability and emphasizes the importance of establishing a data culture within organizations. Takeaways Start early with data observability to ensure accurate and reliable analytics and decision-making. Data observability is a collaborative process that requires the proper tooling, defined processes, and a data-driven mindset. LiTech offers a user-friendly data observability solution that automates data validation, detects anomalies, and provides insights on data quality. Companies should prioritize data literacy and SQL skills to implement data observability effectively. Establishing a data culture and involving the data team in decision-making is crucial for successful data observability implementation.

Have you ever wondered what happens behind the scenes in organizing conferences? In this episode, we have Aidis and Inga, who are organizers of PyCon LT (probably the biggest Python event in the region!). Tune in to the tips on how to get your talk into the conferences, if Chat GPT can help you write an abstract and description, and what other Python conferences are a must to see! PyCon Newsletter Registration link: https://mailchi.mp/33c3df7619af/pyconlt-2019 PyCon.lt Website: https://pycon.lt/2024

Welcome to another engaging episode of our podcast series! In this special edition, we're thrilled to have Tomas Ivanaitis, the head of data engineering at Surfshark and a mentor par excellence. Tomas's journey in the dynamic world of data is about technical growth and nurturing leadership qualities. 🔍 What's Inside: Journey Through Data: Tomas unfolds his narrative, transitioning from programming to mastering data engineering. Leadership in Data: Gain insights into how data engineering intertwines with effective team management and leadership skills. Mentoring the Next Gen: Learn from Tomas's approach to mentorship, shaping the future of data professionals. Crafting High-Performance Teams: Discover the art of building and leading powerful data teams in a rapidly evolving tech landscape. 📈 Why Tune In? This episode is more than just a conversation; it's a reservoir of lessons, experiences, and wisdom for anyone passionate about data, leadership, and career development. Don't miss out on these invaluable insights from one of the leading minds in data engineering! #DataEngineering #CareerGrowth #Leadership #Mentorship #TechPodcast

Join us in this enlightening episode as we sit down with Robert Hodges, a seasoned expert in databases and programming. We delve into the fascinating evolution of programming languages, discussing the rise of Rust, the dominance of Java in the US, and C++'s stronghold in Eastern Europe. Robert offers a deep dive into ClickHouse, highlighting its unique development in C++ and its seamless integration capabilities with Kafka. We explore the universality of SQL, its enduring relevance, and the challenges its syntax presents, even to seasoned developers. For those keen on expanding their knowledge, Robert recommends the transformative book "Java Concurrency in Practice" by Brian Goetz, which sheds light on Java's concurrency features and the intricacies of the Java memory model. We also touch upon the evolution of Perl, drawing parallels with languages like COBOL, and reflect on the invaluable role books have played in the journey of many developers. Whether you're a database enthusiast, a programming language aficionado, or someone keen on the intricacies of data processing, this episode promises a wealth of insights. Tune in!

In this episode, Niko Korvenlaita and Tomas Peluritis discuss the importance of accurate data processing, the role of data engineers, and the significance of aligning data projects with business needs. They explore data modelling, semantic layers, and the power of metadata in making data more accessible. Plus, discover their top book recommendations for diving into the world of data.

In this enlightening episode of my podcast, join me, Tomas Peluritis, as I engage in a captivating conversation with Rytis Jonas Zolubas, a seasoned data professional. Together, we dive deep into the realm of data consultancy, sharing our collective wisdom and experiences to guide both data consultants and companies seeking consultancy services. Through our dialogue, we explore the pivotal moments that prompt professionals to shift from full-time roles to consultancy, the nuances of consultancy work, effective strategies for client interactions, the dynamics of holiday management in the consultancy world, and the industries that frequently leverage consultancy expertise. Rytis and I offer candid anecdotes, practical advice, and valuable insights, making this episode a must-listen for data enthusiasts considering a consultancy path or businesses in search of external data insights. Tune in to gain a comprehensive understanding of the intricacies of data consultancy from the perspectives of two seasoned industry insiders.

While doing my podcast in Lithuanian only, I was looking for companies who, in my eyes, should be interesting to talk about how they work. I've heard about Hostinger in different contexts, and one thing led to another, and I'm talking to Valentinas. It was very interesting to hear how they operate, their data teams structure, its position in the company and how the hiring process looks. If you want to hear it yourself - tune in to this episode, and happy listening!

Barbora is an eCommerce business in Lithuania that delivers groceries to your doorstep. For quite a while, it was interesting to me how in such a company, a data team is operating. I approached Andrius some time ago, but then we lost touch (holidays, busy days, etc.), so after a while, we circled back and caught up on all of these topics. As usual, for these kinds of series, we covered structure, ways of working, the hiring process and how the team operates. Happy listening!

Pydantic, I didn't know about this library up until like mid of last year when one candidate sent a task with this library used, then there was a boom in Linkedin that it's being rewritten in Rust for v2. Got my opportunity to talk to its creator Samuel Colvin during PyCon LT 2023. Was a blast for me; listen in on what we talked about!

Corner Case Technologies started to appear in my LinkedIn feed, first because of Python meetups, then because of a Python internship. Stars aligned, and I had an opportunity to talk to Justinas Kuizinas (CTO at Corner Case Technologies) about these things and more!

Ritchie Vink - author of Polars, Marc Garcia - pandas core developer. But no, I didn't invoke the dataframe war in this talk. Was interesting to hear their perspectives on things, the future of dataframe landscape and much more. Not going to do any spoilers, so tune in!

Vienas iš tikrai gerai visiems žinomų startuolių "Trafi". Su manimi sutiko pakalbėti Dominykas Sedleckas, šiuo metu einantis CTO pareigas. Smagu susipažinti ir išgirsti kokius pomėgius turi mano kalbinami žmonės. O jei jau einam prie tinklalaidės reikalų: buvo įdomu sužinoti kokia duomenų komandų istorija šioje įmonėje, kaip vyskta darbinimosi procesai. Smagu visada išgirsti apie įmonių transformacijas ir kaip jos vyksta (arba dėl ko prasidėjo), tad "Trafi" šiuo metu irgi juda prie kitokių duomenų komandos struktūrų ir veikimo principų. Na, o jūs paklausykit patys, kaip jiems sekasi, ką jie veikia.

Dažnai bent mano LinkedIn sraute matau informaciją apie įmones iš šios grupės. Mano žiniomis labai stiprius specialistus turinti įmonė. Žinant, kad rinka yra labiau Jungtinėje Karalystėje, buvo įdomu išgirsti kaip  įmonė atsirado Lietuvoje. Ir tikrai nepamiršom svarbios temos apie  duomenų komandas ir darbo principus. Smagaus klausymo!

Spalvinga ir gerai žinoma įmonė Kilo.Health, turinti daugelį produktų.  Man asmeniškai pačiam buvo labai įdomu kaip struktūrizuotos komandos ir  kaip jos dirba. Pamaniau puiki proga išgirsti tai iš Petro Šeikos.

Tęsiu pokalbius su įvairių įmonių atstovais ir duomiuosi jų duomenų  komandų sudėtimis, veikimo principais ir darbinimosi procesais. Šį kartą  pakalbinau Audrių Kučinską iš CarVertical. Asmeniškai labai patiko ką  išgirdau. TIkiuosi patiks ir jums!

Šiai tinklalaidei pasikvieičiau Gytį Repečką, kad pasidalintų savo mintimis ir požiūriu apie atvirojo kodo programas ir duomenų modeliavimą. Atvirojo kodo programos tampa kai kurių įmonių pagrindiniu produktu. Pavydžiui Astronomer, Databricks, Preset ir daugelis kitų. Įdomu buvo bendrai sužinoti daugiau informacijos apie tai iš žmonių, kurie daugiau žino. Papildomai dar palietėme kitas temas kaip privatumas ir etiniai socialiniai tinklai. Bet tinklalaidės pagrindinė tema buvo duomenų modeliavimas. Palietėme daugybę pasirinkimų nuo žvaigždės/snaigės schemų iki Data Vault ar normalizuoto duomenų modelio. Pakalbėjom ir apie lakehouse ir bendrai, kaip ankstesnės tiesos, kurios prasidėjus didžiųjų duomenų erai buvo nurašytos kaip atgyvenos, dabar grįžta atgal. Gyčio minėtos knygos: MEIER, Andreas; KAUFMANN, Michael. (2019) SQL & NoSQL Databases. Wiesbaden: Springer Vieweg. ISBN 978-3-658-24548-1 W.H. Inmon, Daniel Linstedt, Mary Levins (2019) Data Architecture. A Primer for the Data Scientist. Second Edition. Elsevier. ISBN 978-0-12-816916-2 Alex Petrov (2019) Database Internals. A deep dive into how  distributed data systems work. O'Reilly Media. ISBN 978-1-4920-4034-7

Ar jums kaip ir man kyla klausimų ką žmonės ir kaip bendrai veikia Turing College? Mano akimis vienas iš garsesnių data ruošimo platformų. Pakalbinau Giedrių Žebrauską (Head of Education) įvairiais susijusiais klausimas. Jei įdomu ir jums - siūlau pasiklausyti. 

Ar nekilo klausimų, ką veikia debesijos inžinieriai? Kokių sugebėjimų reikia turėti norint tokiu tapti? O Duomenų infrastruktūros inžinierius? Šį kartą į svečius pasikviečiau Saulių Grigaliūną padėti atsakyti į šiuos ir kitus eteryje skambėsiančius klausimus. Smagaus klausymo! 

Naujas formatas, kur kalbinu įvairių duomenų sričių žmones. Šį kartą kalbinu Mašininio mokymosi inžinierių Eligijų Bujoką. Jo LinkedIn: https://www.linkedin.com/in/eligijus-bujokas-a27676120/ Medium: https://eligijus-bujokas.medium.com/

Įžanga į tinklalaidę, kodėl rinkausi tokį formatą ir t.t. Plačiau apžvelgiu ką veikia duomenų inžinierius, kokias problemas sprendžia, už ką atsakingas ir t.t.