Michael E. Driscoll @medriscoll Twitter profile

Last Seen Profiles

@edusilvafogo

@pent_Mosa

@CoachMamsUD

@_BBBuzz

@elliotthaut

@SaveVsTPK

@teamtelevixen

@mabeizz

@ta_tadesu

@valenl0ves

@Jasonm03

@Dosinda961308

@JFootballwine

@mfstash

@jakesaranghaeee

@PeepAhsiaOut

@thesadmas

@OloruntoGabrel

@MkoloniB

@urlmoji

@RorRajanyagana

@julianflores34

@antalyailtarim

@sasae_7

@Nudeway_

@TheOfficeMystic

@princessboujiee

@ColinInCOMO

@momyfwbs

@JCM_MDPI

@UAhmedoglu

@shima_kawasaki

@gigixhunter

@RJSonam

@yuna79116048623

@codeerror_

Michael E. Driscoll

@medriscoll

9 months

Bank: We're going to need a wet signature on this form. Please print, sign, scan, and send back to us. Me: % brew install ImageMagick % convert -density 90 bank_form.pdf -rotate 0.5 -attenuate 0.2 +noise Multiplicative -colorspace Gray scanned_form.pdf

23

129

2K

Michael E. Driscoll

@medriscoll

2 years

“Have you ever tried multiplying roman numerals? It’s incredibly, ridiculously difficult. That’s why, before the 14th century, everyone thought that multiplication was an incredibly difficult concept, and only for the mathematical elite."

18

98

999

Michael E. Driscoll

@medriscoll

2 years

"Then arabic numerals came along, with their nice place values, and we discovered that even seven-year-olds can handle multiplication just fine. There was nothing difficult about the concept of multiplication — the problem was that numbers, at the time, had a bad user interface."

5

28

452

Michael E. Driscoll

@medriscoll

9 months

Today @Motherduck , the company behind @duckdb , announced that they've raised $100mm. Yesterday, @tabulario , the team behind Apache Iceberg, announced a fresh $26mm round. And last week Databricks added $500mm to its coffers. What is happening?! What I believe we are now

4

46

360

Michael E. Driscoll

@medriscoll

1 year

Dashboard design philosophies.

12

36

264

Michael E. Driscoll

@medriscoll

8 months

This morning I was lucky enough to catch up with @duckdb creator @hfmuehleisen . I asked him the most surprising pattern he's observed for DuckDB in the wild. He shared that it's not just interactive use cases that are driving adoption, such as powering faster data applications

10

41

261

Michael E. Driscoll

@medriscoll

2 years

- Bret Victor ( @worrydream ) quoted in

What Will Software Look Like Once Anyone Can Create It?

A former YouTube executive recalls people being mystified on why he joined a company best known as a platform for badly-produced cat videos. He foresaw a time when YouTube would disrupt online video,...

hbr.org

6

23

245

Michael E. Driscoll

@medriscoll

9 months

The "structured versus unstructured" taxonomy is outdated and unhelpful, a shibboleth of the Hadoop era. Data infrastructure today is dominated by *structured* data: JSON events, Kafka payloads, Postgres CDC logs, Hive-partitioned buckets of Parquet. "Modeled versus

18

21

233

Michael E. Driscoll

@medriscoll

3 months

Today @ClickHouseDB announced they're moving into the embedded OLAP engine space, with their acquisition of @chdb_io , and directly competing with @duckdb . Why is this a big deal? Because @chdb_io , like @duckdb , provides a cheaper, faster, and SQL-ier alternative to Spark for

Tanya Bragin

@tbragin

3 months

Could not be more excited to have @Auxten join forces with us to focus on @chdb_io (in-process version of @ClickHouseDB ) full time! How are you using chDB? What do you want us to focus on next? Share your ideas here as we embark on this journey together:

2

9

58

3

31

180

Michael E. Driscoll

@medriscoll

1 year

"SQL + YAML = dashboard" officially launched today by @rilldata . A BI-as-code stack controllable via git, powered by @duckdb . Ask and ye shall receive @josh_wills .

Rill 0.16 – SQL + YAML = Dashboard | Rill

⚡ Rill Developer is a tool that makes it effortless to transform your datasets with SQL and create powerful, opinionated dashboards. These are our release notes for our 0.16 release, still in Tech...

docs.rilldata.com

Josh Wills

@josh_wills

2 years

While I wait for @TopcoatData to be open-sourced, what is my best declarative, SQL+yaml way of creating a simple dashboard against DuckDB? @RillData do y’all have a way to help me out here?

7

2

33

9

23

155

Michael E. Driscoll

@medriscoll

1 year

So @DuckDB 's native format is 4x faster than Parquet, but 2x larger on disk. CSV is a poor performer across the board. Blog post: (Also discussed In our Discord channel here )

Manipulate big data with Arrow & DuckDB | Christophe Nicault

Struggling with memory for your large data sets?We work more and more with large datasets, requiring interoperability between platforms. We must then manage a puzzle, between the storage format,...

www.christophenicault.com

4

21

153

Michael E. Driscoll

@medriscoll

11 years

The only 3 true job interview Qs: 1) Can you do the job? 2) Will you love the job? 3) Can we tolerate working with you? (via @georgebradt )

9

192

149

Michael E. Driscoll

@medriscoll

3 months

The database market is bifurcating into two broad battlefields, with 100s of firms competing for a few trillion dollars of market share, backed by staggering amounts of capital: * A cost war for SQL-at-scale, playing out between warehouses (Snowflake, Oracle) & lakehouses

8

22

145

Michael E. Driscoll

@medriscoll

4 months

Why leverage DuckDB for lightweight ETL pipelines? “Many DuckDB jobs now complete faster than a Spark cluster can start up.”

DuckDB

@duckdb

4 months

@huggingface @fivetran @prequel_co @DataCamp Mike Eastham of @TectonAI talking about Building Tecton's Feature Engineering Platform on DuckDB.

1

2

16

2

12

143

Michael E. Driscoll

@medriscoll

1 year

Apache Arrow began with faster analytics, but is now the core of a new breed of infrastructure (Iceberg, Parquet, Polars, @duckdb ) says @buckymoore : "A new, unbundled OLAP architecture [where] data is stored directly in object storage like S3 or GCS."

Infrastructure in '23

For the third year, Bucky Moore shares what he believes to be the most dynamic and important areas of innovation in infrastructure.

www.kleinerperkins.com

5

10

117

Michael E. Driscoll

@medriscoll

12 years

Insanity is doing the same thing over and over and not coding up a solution.

6

323

107

Michael E. Driscoll

@medriscoll

10 years

Start-up pitch decks are children's books for VCs: short stories told with many pictures and few words.

8

104

108

Michael E. Driscoll

@medriscoll

7 years

If i) more data beats better algorithms & ii) fresh data beats stale data, then the future is not AI, but streaming arithmetic at scale.

9

60

107

Michael E. Driscoll

@medriscoll

1 year

It’s only typed data if it comes from the Parquet region of France, otherwise it’s just sparkling CSV

2

18

108

Michael E. Driscoll

@medriscoll

12 years

"Work on Stuff that Matters. Create More Value than You Capture. Take the Long View." http://t.co/1OzpCbSm An ageless piece by @timoreilly

2

92

105

Michael E. Driscoll

@medriscoll

10 years

Probabilistic data structures: the ideal collections data types at scale. (via @pacoid http://t.co/h1MbHzfjo1) http://t.co/KokFtu9ZmZ

0

51

102

Michael E. Driscoll

@medriscoll

2 years

You can build reliable software on top of unreliable systems. But you can’t build good analytics on top of bad data.

7

13

100

Michael E. Driscoll

@medriscoll

9 months

Data lake architectures continue to rise in prominence with Tabular’s $26m funding announcement. Apache Iceberg, Tabular’s core tech, was forged at Netflix by eng teams wanting to layer a better table API on top of unstructured data lakes. Iceberg is a foundational pillar,

Tabular

@tabulario

9 months

Exciting news! We closed a $26M round of funding from Altimeter, @a16z and Zetta Venture Partners to build our independent data platform based on #Apacheiceberg . We've also have added #GoogleCloud and Amazon Athena support. Read more here:

3

11

70

5

13

97

Michael E. Driscoll

@medriscoll

10 years

Maslow's Hierarchy, 2014 edition. (HT @20002ist ) http://t.co/83oblPabAv

5

138

92

Michael E. Driscoll

@medriscoll

10 years

The internet of things is an internet of streams. Stream processing at scale is the next frontier in data.

8

94

92

Michael E. Driscoll

@medriscoll

2 years

@rbranson

1

2

91

Michael E. Driscoll

@medriscoll

1 year

0

8

90

Michael E. Driscoll

@medriscoll

8 years

The fundamental task of data visualization: mapping words and numbers to the retinal variables of color, shape, and orientation.

3

43

90

Michael E. Driscoll

@medriscoll

1 year

The obsession with @DuckDB has at times resembled a cult following. 🦆🦆🦆 So why did we build @rilldata 's data profiling & dashboard building tool with @duckDB ? A substantive argument deserves more than one tweet. In the following 🧵, I discuss why we chose it in 2021. 👇👇

3

20

88

Michael E. Driscoll

@medriscoll

11 months

Yes, we got rid of the run button in our SQL editor, thanks to @duckdb . No more tapping out SQL, clicking "run", watching spinners, and waiting for results. Just type "SELECT * FROM foo" and the results appear before your finger lifts from the keyboard. @hamiltonulmer talks

5

6

87

Michael E. Driscoll

@medriscoll

1 month

Big news in the data world: Lloyd Tabb, after selling Looker to Google for $2.6B, is now leaving to join... Meta. At first glance, it's an unusual move. Why Meta? Lloyd's latest creation is a "better SQL" called @MalloyDev . Meta offers a crucible for shaping Malloy into

lloyd tabb

@lloydtabb

1 month

“Necessity is the mother of invention”. This coming week I’m starting a new job at Meta to work on Malloy and to bring Malloy into Meta’s internal data tooling.

14

7

186

1

13

86

Michael E. Driscoll

@medriscoll

10 years

Vega.js is the long-awaited complement to D3.js: a declarative grammar for visualization. http://t.co/fyi70UeZm8 http://t.co/yFCQwiQ66e

0

66

85

Michael E. Driscoll

@medriscoll

7 years

"Machine learning is about data and algorithms, but mostly data... & only as good as the data you use to train it."

What does one need to know in machine learning?

Daniel Tunkelang's answer: As someone who often finds himself explaining machine learning to non-experts, I offer the following list as a public service announcement. 1. Machine learning means...

www.quora.com

2

38

85

Michael E. Driscoll

@medriscoll

10 years

Facebook's and Google's massively different tech cultures summed up on two websites: http://t.co/7MjU0mHu7w vs http://t.co/i1iAGmzbia.

5

78

82

Michael E. Driscoll

@medriscoll

11 months

We built an interactive exploratory dashboard of the @duckdb code repository on Github... powered by @duckdb :). Amazing to see the project's acceleration, almost 300 committers have made 29k+ commits, with @mraasveldt @Thijsbruineman , (naturally) @hfmuehleisen , @lnkuiper , and

4

12

81

Michael E. Driscoll

@medriscoll

6 months

DBT has taught an entire generation of analysts that Github, command-line interfaces, and codeful workflows are to be embraced, not feared. BI-as-code is a natural extension of this philosophy further up the stack to data applications and dashboards.

MotherDuck

@motherduck

6 months

Explore the new Bi-as-code trend in data 📊 @mehd_io 's latest blog covers dashboard creation with @duckdb & MotherDuck, and dives into tools like @rilldata , @evidence_dev , and @streamlit . Get coding! 👨‍💻

0

16

63

3

5

79

Michael E. Driscoll

@medriscoll

11 years

Scientists must publish fewer, truer results. The Economist covers the biggest threat to science today: http://t.co/Un11HWOeiZ

8

96

74

Michael E. Driscoll

@medriscoll

3 months

Is anyone building a serverless time-series database? The architecture would be a one-dimensional version of what cloud optimized GeoTIFFs use: tiles across time, with different aggregation levels (minutely, hourly, daily, etc), all backed by an object store. You wouldn't

9

8

75

Michael E. Driscoll

@medriscoll

14 years

Linus Torvalds was born just 72 hours before the Unix Epoch on January 1, 1970. When the machines take over, they'll call him Jesus.

0

337

75

Michael E. Driscoll

@medriscoll

21 days

A smart friend recently asked me: Are vector databases a product or a feature? @Pinecone , @qdrant_engine , @trychroma , @weaviate_io , and @milvusio have raised hundreds of millions and are collectively worth billions. They represent the fastest-growing segment in data

21

8

75

Michael E. Driscoll

@medriscoll

9 months

If you live in NYC, I'm hosting a salon this Tuesday night with ~25 founder/CEOs & CTOs to talk data infra + AI at Manhattan's oldest distillery. We'll be hosting a discussion over drinks led by: * Edo Liberty, founder of @pinecone * Erik @Bernhardsson , founder of @modal_labs

8

5

73

Michael E. Driscoll

@medriscoll

11 years

"Introducing Druid: an open-source infrastructure for real²time exploratory analytics on large datasets." http://t.co/YsLOe5Wle7

3

53

73

Michael E. Driscoll

@medriscoll

6 years

"Linear regression on 100 data points is a statistics problem. Linear regression on 100 million data points is an engineering problem." - @l2k

3

14

70

Michael E. Driscoll

@medriscoll

2 years

Today, I’m excited to share that @rilldata has raised $12mm of capital from a data supergroup of investors to re-imagine how business dashboards are built and used.

TechCrunch

@TechCrunch

2 years

Rill wants to rethink BI dashboards with embedded database and instant UX by @ron_miller

0

3

17

3

12

70

Michael E. Driscoll

@medriscoll

2 months

Sometimes as a data person, you just need to know "What's in that S3 bucket"? No README file, no schema, no Slack discussion can substitute for just a few minutes of just 👀 looking at the data. 👀 So here's a demo of going from Parquet file to Pivot table in less than 60

2

9

69

Michael E. Driscoll

@medriscoll

9 months

Behind every "serverless" offering by startups is usually... a server.

6

5

67

Michael E. Driscoll

@medriscoll

7 months

A killer feature for GitHub would be a more fully integrated object store offering. Many projects reference data in S3. This requires managing a second set of credentials. I want a GitHub storage service, with ghs:// style pointers, and have it just work.

8

3

67

Michael E. Driscoll

@medriscoll

11 years

Design arbitrage: building a better UI on top of sites that suck, and charging a premium. c.f. Seamless, Ticketfly, HipMunk.

6

65

Michael E. Driscoll

@medriscoll

1 year

Reaction to @duckdb 's export-to-Excel feature

1

5

60

Michael E. Driscoll

@medriscoll

8 years

This is the world's oldest time series graph, showing planetary movements, from a 10th century Macrobius manuscript.

0

27

53

Michael E. Driscoll

@medriscoll

9 months

Data lakes are increasingly the foundation of companies’ data infrastructure, so it’s great to see orchestrators like @RudderStack , @bobsled , @AirbyteHQ , and now @fivetran making them first class destinations (with help from @ApacheIceberg , formats like Parquet, and engines like

George Fraser

@frasergeorgew

9 months

Data lake support is one of the most technically challenging things we've ever delivered. Writing updates to S3 requires building a quasi-DWH inside Fivetran. We use @DuckDB to rewrite the parquet files and built a BigQuery-style scale-out service to deal with large tables.

3

11

85

3

8

56

Michael E. Driscoll

@medriscoll

12 years

"Your email inbox is a to-do list created by other people." -- via @cdixon

4

133

54

Michael E. Driscoll

@medriscoll

4 months

The @RillData team was in Brussels for #fosdem , and we rode the train back to Amsterdam with Alexey Milovidov, creator of @ClickHouse . He asked us: "So why don't you scale up Rill on ClickHouse?" So here we are: interactively exploring a decade's worth of Wikipedia traffic

Tanya Bragin

@tbragin

4 months

. @RillData operational BI vision really resonates with me: beautiful, immersive, SQL-driven BI-as-code. 😍 Sneak peek into a PR in the works. On the picture: instant queries on a dataset of 480,933,298,381 (half a trillion) records in @ClickHouseDB 🚀

0

9

59

0

11

55

Michael E. Driscoll

@medriscoll

2 years

The line between localhost and cloud is blurring. Apps like Figma & Notion leverage local compute but with transient local state, backed by cloud, for a fast, responsive UX. WASM unleashes this same power for web apps. An M1 chip is a terrible thing to waste.

2

6

53

Michael E. Driscoll

@medriscoll

1 year

With @duckdb , we can skip the data warehouse and build blazing-fast analytics *directly* on Apache Parquet files in S3 or GS, no ETL necessary. Go from 10GB Parquet --> interactive pivot table in the browser, in seconds. Cloud scale meets MacBook M2 speed.

Speros Kokenes

@sperosck

1 year

Prototyping pivot tables with @duckdb this week Shoutout to @mraasveldt and @__AlexMonahan__ for the SQL help!

3

56

1

4

52

Michael E. Driscoll

@medriscoll

9 years

Hard lesson for first-time tech founders to learn: great product serves its users, not its creators.

4

50

Michael E. Driscoll

@medriscoll

1 month

Jeff Bezos famously quipped, "Your margin is my opportunity." In data infrastructure, the profit margins of Snowflake and Databricks are an opportunity for the SQL-on-object-store insurgents: Tabular, MotherDuck, and others. So here's a prediction...

4

3

51

Michael E. Driscoll

@medriscoll

7 months

Tomorrow night inside the Twitt(er, X) HQ in SF, @rilldata is hosting a salon with dozens of founders, builders, & innovators in the most exciting niche in data: serverless infrastructure. (DM me if you'd like to join us). Why is this creative surge in data infra happening?

6

9

50

Michael E. Driscoll

@medriscoll

5 months

Spotlight vs lantern intelligence in analytics. One of the root causes of dashboard sprawl in companies is applying a "spotlight" philosophy to business questions. What were our top-selling products last week? Here's a Top-Selling Products dashboard. Which cohorts are

0

7

50

Michael E. Driscoll

@medriscoll

10 years

Every startup needs two conference rooms: Shabby, with exposed ducts, for meeting vendors; Shiny, with Aeron chairs, for pitching prospects.

7

30

47

Michael E. Driscoll

@medriscoll

3 years

All data is time-series data.

11

5

50

Michael E. Driscoll

@medriscoll

4 months

3

7

50

Michael E. Driscoll

@medriscoll

7 months

If you're a startup, the ability to make sense of your unit economics at a customer-level is a superpower. But it's a deceptively hard problem to solve. Why? The heart of the matter is the mismatch between your pricing model and your cost model. You price on one set of axes

Tom Blomfield

@t_blom

7 months

Here's an idea I wish someone would build: Mixpanel-style analytics for customer unit economics. At @monzo , we had an event-driven data architecture that allowed us to assign cost or revenue to every action a customer might take. Spend £120 on a debit card in NYC? £2 of

56

83

1K

2

6

49

Michael E. Driscoll

@medriscoll

26 days

Data startups love building demos on publicly available data sets. But in my experience, no one uses these demos. Demo data is to data tools what Lorem Ipsum is to publishing tools: nearly useless. If you want to get someone excited about your tool, they need to see how

10

7

49

Michael E. Driscoll

@medriscoll

8 years

Data scientist, n. Human janitor for machine intelligence.

1

27

45

Michael E. Driscoll

@medriscoll

10 years

"Be obstinate about your vision, but flexible with your tactics." - @vkhosla

1

53

46

Michael E. Driscoll

@medriscoll

1 year

. @hamiltonulmer recently gave the first ever live demo of @rilldata at @BrowserTech SF. He shows what's possible when you combine modern browsers + @duckdb + BI-as-code philosophy... with Midjourney slides to boot!

2

10

48

Michael E. Driscoll

@medriscoll

3 years

Fascinating tour of the modern data stack running at AirBnB, through the lens of Minerva, their data modeling middleware. “Define metrics once, use them everywhere.”

How Airbnb Achieved Metric Consistency at Scale

Part-I: Introducing Minerva — Airbnb’s Metric Platform

link.medium.com

0

5

46

Michael E. Driscoll

@medriscoll

7 years

The first step of data visualization is to ask: is visualizing the data even necessary? A well-designed table often outperforms a graph.

8

30

47

Michael E. Driscoll

@medriscoll

3 months

Fast databases like @ClickHouseDB deserve fast dashboards. We're excited to announce that as of our 0.41 release, @RillData dashboards can now run on @ClickHouseDB . With this live connector, ClickHouse users can instantly transform any table into an exploratory dashboard,

1

8

45

Michael E. Driscoll

@medriscoll

1 year

The future of data sharing APIs is statically-hosted parquet files on object stores.

Robin Linacre

@RobinLinacre

1 year

1/ Bulk open data is best served as statically-hosted parquet files, with csv equivalents. It's faster, easier to use and cheaper to host than alternatives such as custom APIs. New blog: Am I missing something? So you agree? Interested in views!

11

30

194

3

5

44

Michael E. Driscoll

@medriscoll

7 months

OpenAI board: How can we bring the “non” back to this nonprofit?

2

6

43

Michael E. Driscoll

@medriscoll

9 years

InfluxDB, OpenTSDB, or Druid - which open-source time-series DB is best? "Know your use case", says @CriteoEng :

PolyConf 14: Druid @ Criteo / Gregory Letribot & Julien Lavigne du...

How do you monitor performance for one of your clients on a specific user segmentation when dealing with billions of events a day ? With over 2 billion ads s...

www.youtube.com

0

7

41

Michael E. Driscoll

@medriscoll

4 months

WYSIWYF (What You See Is What You Fetch) is my new preferred acronym for lazy query evaluation / deferred loading of data in scrollable, interactive tables in @rilldata ... (About to go on stage at #fosdem2024 in Brussels to talk about this + other strategies for keeping data

2

5

42

Michael E. Driscoll

@medriscoll

7 months

Not just S3, but other object stores such as Azure Blob Service, Google Cloud Storage, and increasingly, Cloudflare R2 all offer cheap, reliable, vast storage, attachable to serverless compute metered by the millisecond. This will reshape cloud infrastructure.

Davis Treybig

@TreybigDavis

7 months

S3 is increasingly becoming the default storage layer for cloud infrastructure. I wrote notes on this trend, its benefits, its challenges, its early adopters, and the opportunity it presents for new startups to disrupt large infrastructure categories

16

35

201

2

41

Michael E. Driscoll

@medriscoll

7 months

VCs as board members: maybe not a bad idea after all.

3

4

41

Michael E. Driscoll

@medriscoll

2 years

Postmodern Data Stack: a serverless approach that builds at run-time a pipeline, database, and data application. No stateful infrastructure required. (HT to @matsonj whose epic MDS-in-a-box thread yesterday inspired this work by David.)

David Gasquez

@davidgasquez

2 years

Spent some time simplifying a PoC I did a while back stithing together @getdbt , @duckdb , and @RillData . It works on Codespaces/Devcontainer! More info in the README.👇

2

5

47

3

4

40

Michael E. Driscoll

@medriscoll

11 months

Where @DuckDB SQL goes, others follow: now Snowflake has adopted the superior ergonomics of DuckDB's GROUP BY ALL expression. Dare I call it imprinting...

Felipe Hoffa @[email protected]

@felipehoffa

11 months

New in @SnowflakeDB 's SQL: GROUP BY ALL This saves time and prevents errors, as the compiler figures out the columns that need aggregation. E.g., in the pic GROUP BY ALL takes cares of the query - instead of "GROUP BY tag, answered, year" or the obscurer "GROUP BY 1, 3, 4".

9

20

221

3

4

40

Michael E. Driscoll

@medriscoll

4 years

@villi For five years my wife has asked if she could Docusign the IRB (medical research) approvals at her hospital, and was told no. Last week, they introduced Docusign.

0

1

38

Michael E. Driscoll

@medriscoll

3 months

Code-first products present an unreasonably effective interface to AI models, because AIs excel at generating the very code these products run on. Today's release of Rill 0.41 introduces a related, powerful side effect of our BI-as-code philosophy: You can now create an

2

10

39

Michael E. Driscoll

@medriscoll

3 years

Cloud data warehouses like Snowflake offer cheap storage, but expensive (and at scale, slow) access. Data stores like Druid, Pinot, and Clickhouse offer expensive storage, but cheap (and fast!) access. Choose the right database for your application.

0

9

38

Michael E. Driscoll

@medriscoll

10 years

I agree: "the world is time-series." Nice survey of time-series databases. http://t.co/iAU9gY1Qdp (TempoDB, OpenTSDB, SkyDB, Druid)

1

18

37

Michael E. Driscoll

@medriscoll

13 years

Seven data-mining algorithms which are 200-400x faster on GPUs: http://bit.ly/dV7uXr

0

28

38

Michael E. Driscoll

@medriscoll

9 years

Productivity hack: when writing, turn off wifi on your laptop, satisfy any "let me just look that one thing up" urges with your phone.

3

12

35

Michael E. Driscoll

@medriscoll

4 months

To kick off our sponsorship of DuckCon #4 tomorrow in Amsterdam, we created this ~45 second video showing how the blazing speed of @duckdb powers a radically new kind of BI experience via @RillData . Instant slicing & dicing, automatic visualizations, interactive pivot tables, &

0

8

37

Michael E. Driscoll

@medriscoll

9 years

Introducing Facet: A New Interface & Query Engine for High-Dimensional Data http://t.co/c9u2nAHVZW

4

11

37

Michael E. Driscoll

@medriscoll

12 years

Data scientists: better statisticians than most programmers & better programmers than most statisticians http://t.co/rp4z0Jt6 @peteskomoroch

3

38

36

Michael E. Driscoll

@medriscoll

10 years

The 9 Best Languages for Crunching Data http://t.co/o0ojlExrrg (trade-offs of sophistication, scale, speed, & simplicity)

4

30

35

Michael E. Driscoll

@medriscoll

10 years

The sad truth about data APIs is that most are afterthoughts: poorly documented and fragile. Data APIs should be first-class products.

3

41

36

Michael E. Driscoll

@medriscoll

3 years

Machine learning algorithms are best suited to replace humans in systems with decisions that are fast, frequent and -- most importantly -- inconsequential if wrong. So we should stop obsessing about high-death-potential autonomous driving until we've nailed autonomous vacuuming.

4

5

34

Michael E. Driscoll

@medriscoll

13 years

Overdraft fees are a bank’s way of saying, “Hi, we noticed you are out of money, so we charged you more money.” - http://t.co/3fIv9nuu

3

234

35

Michael E. Driscoll

@medriscoll

3 years

@mattturck 3 years into building a startup, board meeting with new Series A investor.

2

5

35

Michael E. Driscoll

@medriscoll

3 months

I recently joined @ericdodds and @KostasPardalis on The Data Stack Show to chat OLAP engines and BI. Here the tl;dr of what I said to save you 57 minutes of your life: * Long live OLAP - Fast OLAP engines make dashboards awesome; but scaling up OLAP is hard (c.f.

2

9

35

Michael E. Driscoll

@medriscoll

8 years

My new Op-ed: Four Pillars of Managing Extraordinary Engineers. Thx @aroetter @vgill for the advice

Engineering management may be the most unnatural act of all | TechCrunch

When it comes to software engineering, that management is best which manages least -- to borrow Thoreau’s quip about government. While it’s rarely as easy as nodding at a brilliant developer and...

techcrunch.com

2

17

34

Michael E. Driscoll

@medriscoll

2 years

Open-source projects stand on the shoulders of giants, or in our case, 🦆🦆🦆. The @rilldata dashboard tool is powered by @sveltejs and @duckdb . Try it yourself: curl -s | bash

Marissa Gorlick

@marissagorlick

2 years

Today's release of @RillData Developer includes the ability to search for dimension values and choose whether to exclude or include them. These new features make a powerful addition to the dashboard experience that will help you find the right insights faster than ever.

2

4

28

0

5

35

Michael E. Driscoll

@medriscoll

9 years

One of the strongest signals of quality for any software framework is the clarity of its documentation.

2

18

34

Michael E. Driscoll

@medriscoll

2 years

"The data science community is reinventing DBMSs... poorly." - @hfmuehleisen @duckdb changes that, with a state-of-the-art analytical DBMS that runs blazingly fast on your M1 laptop. Making data fast makes humans happy.

2

4

32

Michael E. Driscoll

@medriscoll

7 years

Spark on Mesos at Scale: Lessons from launching 400,000 executors weekly to process petabytes at @Metamarkets .

Home - Metamarkets

metamarkets.com

1

20

34

Michael E. Driscoll

@medriscoll

10 years

In the city of data, dashboards & visualizations are the glamorous, gleaming towers; ETL is the underground sewers, vents, and wiring.

3

44

34

Michael E. Driscoll

@medriscoll

4 months

The video from our lightning talk "Flying Fast at Scale with DuckDB" at #FOSDEM last weekend in Brussels is here! We speed run through how we've optimized @RillData and @duckdb to deliver an operational BI tool that sparks joy. We do a live demo, discuss our 3-in-1

0

3

34