Curious..about data

I attended my 16th PASS Summit this November 6th, 2019 at Seattle. It was a wonderful week of learning and networking. Below are my takeaways for key days.

The keynotes by Rohan Kumar from Microsoft on wednesday, and Tarah Wheeler, Cyber Security Expert on Thursday were not ‘among the best’, they were ‘THE BEST’ i’ve seen in 16 years. I’ve summarized Rohan’s keynote here.
Tarah’s was basically a warning and an overview on the highly complex terrain of data security, with its many contradictions and ethical struggles.Tarah herself was a role model speaker, who did not bat an eyelid when power went down briefly on her on stage. Her slides were excellently done and her talk precise,crisp, and had us on the edge through every minute of it.
I had the privilege of joining some other ladies in community for a private dinner with our WIT Panel guest Lashana Lewis. I have not had a trivial number of challenges myself but I was amazed at how much she had to face as a black woman in tech to break through. Her work and her words had a huge impact on the listeners at the luncheon on Thursday. I must not fail to mention here that SentryOne has been a sponsor of these luncheons for a several years now(thank you!). The quality of lunch is extra good as well.
The recordings are available here, and will include these keynotes. I highly recommend ordering them if you haven’t already.

The other technical sessions I attended were as below. The recordings include these too.
1 Intelligent Query Processing (taught excellently by Hugo Kornelis)
2 Batch processing mode on Row Store (learned how this works from Niko Neugebauer)
3 Accelerated Database Recovery (Pam Lahoud did a great job showing how this works)
4 Azure Data Studio and Notebooks (New tools made by my dear friend Vicky Harp and her team)
5 How to design and maintain a cloud friendly data warehouse (brilliant session by Ike Ellis)
6 SQL Server on Linux (there were many sessions on this, but being a beginner to Linux I found Randolph West’s session the best)

In addition to this, I re-learned execution plans from Erin Stellato, how to avoid RBAR processing from Jonathan Kehayias, and irreverant ways of enforcing best practices on SQL Server from Rob Volk. There were a couple of vendor sessions which I went into accidentally and had to leave half way.

I cannot possibly write a summit overview without the benefits of networking. Networking is by far the key benefit of attending a conference like this. As a repeat attendee, I have learned to reach out to friends I already know beforehand and make sure I have a meeting with them on my calender. It is really easy to get busy and forget all about priorities. My friends are my priorities and I was glad I look care of that. I was also able to meet several people who are new or perhaps less known, and was able to add them to my network.

I’d like to complete this overview with a few lessons on making the most of the summit:

1 Get there a day before if possible – if you are on a different time zone. In today’s world it is possible to work remotely. It takes time for our bodies to adjust and also to adapt to a crazy schedule ahead. I usually take a day off and get myself acclamatised to what is to come. I know this may not be possible for many people – but I would recommend doing it if possible.
2 Pay attention to keynotes – especially microsoft keynotes. The days are gone when we could sleep in through what used to be mostly commercial and somewhat dry presentations – there are a lot of new terminologies to get familiar with. It also helps to understand how SQL Server is a product is evolving/growing in the market. It also helps to stay on twitter and follow what people say on keynotes. I’ve gotten some really cool insights from tweet feedback.
3 Make a schedule before hand, don’t try to wing it. There are too many sessions and just walking into something randomly can be a miss on a great in person session that would have given much value. Yes, recordings exist, but are a tad below a real class taught live by an expert. Besides, you get to introduce yourself to the speaker and add value to your network. I was glad to have spent time picking sessions I wanted to attend.
4 Reach out to people you know and set up time to talk to them. Sometimes encounters happen by chance, many times we can totally miss talking to people we rarely see. Intentional networking has high benefits.
5 Last but not the least, never neglect self care. Getting flu shots before, taking whatever makes one comfortable (I carry my fleece blanket wherever I go),staying in touch with loved ones, retiring when the body says ‘am done’, are hugely important. Well known author Stephen Covey talks of driving without having time for getting gas – neglecting self care is exactly this.

That is it for this year. Below are some pictures from my experience. Look forward to Summit 2020 at Houston, Texas. Thank you to everyone who made this year’s event valuable and worth attending.

I’ve been at the bloggers table for two years now. I felt honored to be selected this year too. The day has started a bit differently – bloggers were given an overview of what to expect from the board and staff of PASS. It was a very different and great move, in my opinion. It is 8 10 AM now on 6th of November 2019. We are waiting to get started.

Grant kicked off the keynote talking of how different summit is this year and how to take advantage of networking opportunities, of which I could say volumes.

I live-tweet more than live-blog as it has a better reach and many people can read it. But to summarize – a lot of yesterday was on cool features of 2019, including CosmosDB. Big Data Clusters, SQL for iOT(‘Edge’), Accelerated Database Recovery, Intelligent Query Performance and so on. We got to know some cool numbers like over 50 million databases are currently on Azure, and that we can support around 30 replicas as AG secondaries. (Just because you can…). We also learned some interesting terms like Synapse Analytics – which is the third generation Azure DataWarehouse, and Azure Arc – which is the new deployment process for Azure.
Aside from all the cool tech, I was hugely impressed by the attempts at diversity – several women of color presented and demoed stuff to us. In my 16 years of summit I have not seen this many key women (usually you had one or two who were sidekicks to the lead male presenter). Consider following some of these amazing women – Shreya Verma Kale, Anna Thompson and Sri Chintala. Well done on diversity, Microsoft.

Look forward to the second day’s keynote. Follow me here for real time updates.

In the previous post I explored a query on how to construct a basic family tree with sql graph – including table set up and queries. In this post am going to explain how to query this to get relationships and some clues on DNA/ethnic mix.
1 Relationships: We can use the ‘shortest path’ clause to find how people are related in this database. So, if I want all the people a character named Jerusha Hale is related to – I can say this –

SELECT fromperson.name as Fromperson,STRING_AGG(f.remarks+' '+toPerson.Name, '->') WITHIN GROUP (GRAPH PATH) AS FriendConnections,
          LAST_VALUE(toPerson.Name) WITHIN GROUP (GRAPH PATH) AS FriendName,
          COUNT(toPerson.Name) WITHIN GROUP (GRAPH PATH) AS levels
		  
FROM
          PersonNode AS fromPerson,
          PersonRelatedTo FOR PATH AS f,
          PersonNode FOR PATH AS toPerson
WHERE
        
		 MATCH(SHORTEST_PATH((toPerson<-(f)-)+fromPerson))
		 AND fromPerson.Name = 'Jerusha Hale'
    

This is perfectly cool – it tells us who is she is married to, who her parents are, who her grandparents are, cousins are and so on. There are a few things to watch for though, here –

1 I chose not to store derived relationships like grandparents, cousins etc, because that is too much work. So what is pulled has some roundabout derived relationships like row 8, Malama Kanakoa is her grandmother but is being referred to in two steps, she is the daughter of her mother who is the daughter of her grandmother. In a real geneological database, these relationships may be defined more clearly/straightforward ways.
2 If you choose to store derived relationships, it might also be a good idea to store some kind of criteria to it that indicate if the person is immediate family or extended family or something similar. SQL Server will not know that a spouse is a closer relationship than a cousin, for example. And there may be many situations where this priority is important to distinguish.
3 Shortest path only pulls one relationship between two people(or ‘nodes’). For example, Jerusha could be someone’s sister and her sister could be married to her husband’s brother, say, then you will only get one relationship show up here. We have no control over what SQL Server chooses to show. This is a disadvantage and something to be aware of.

2 How to calculate ethnicity percentage, knowing the family tree?

Quite a lot of us think of ethnicity percentage as a 50-50 or an even match between parents somewhat. This is actually very erroneous. We can’t exactly tell how much of our ancestor’s DNA we receive, and the mileage may vary depending on many factors. There is a reason why Geneology is a business and a science in of itself. It is very complex and difficult to understand inherited patterns across many years. That said, 50% may be considered an average from each parent for mundane understanding. So the farther we go, the lower this percentage gets across multiple grandparents. This is a useful table as below:

Level	# from Me	100%	DNA per parent
1	2	Parents	50%
2	4	Grandparents	25%
3	8	Great-grandparents	12.50%
4	16	Great-great-grandparents	6.25%
5	32	Great-great-great-grandparents	3.12%
6	64	Great-great-great-great-grandparents	1.56%
7	128	Great-great-great-great-great-grandparents	0.78%

It needs a very detailed family tree to have all this information on every ancestor, even going back 5 levels. But given what is available – in this test data set for example – a character named Bromley Hale has some ancestors 7 levels away. I used below query to arrive at this.

DECLARE @Familydaughter TABLE(ID int, daughterID int)
DECLARE @Familyson TABLE(ID int, sonID int)
DECLARE @personid INT, @personsonid INT
SELECT @personid = personid FROM dbo.personnode WHERE name = 'Bromley Hale II'
INSERT INTO @Familydaughter
(id,daughterid)
select p1.personid,p.personid
FROM dbo.personnode p, dbo.personrelatedto r, dbo.personnode p1
where match(p-(r)->p1) and (r.remarks = 'daughter of')

INSERT INTO @Familyson
(id,sonid)
select p1.personid,p.personid
FROM dbo.personnode p, dbo.personrelatedto r, dbo.personnode p1
where match(p-(r)->p1) and (r.remarks = 'son of')

;WITH FamilyCTE
AS
(
SELECT 
@personid as ID,
1 AS Level,
null as sonid,
null as daughterid
UNION ALL
SELECT 
m.ID, 
Level+1,
null,
m.daughterid
FROM @Familydaughter AS M
INNER JOIN FamilyCTE c ON m.daughterID = c.ID
UNION ALL
SELECT 
f.ID, 
Level+1,
f.sonid,
null
FROM @Familyson AS f
INNER JOIN FamilyCTE c ON f.sonID = c.ID 
)

SELECT distinct p.name,p.born,p.died, q.level, p.sex,p.origin
FROM familyCTE Q
INNER JOIN dbo.personnode p ON q.id = p.personid
LEFT JOIN dbo.personnode M ON q.daughterid = m.personid
LEFT JOIN dbo.personnode F ON q.sonid = f.personid
order by q.level,p.name ;

Two of his ancestors 7 levels away seem hawaiian/native, so he may be perhaps, 1.56% Hawaiian, or has a wee bit of hawaiian blood and the rest of him is probably American or significantly unknown. The more data we have the easier it will be to calculate this, although this is only mundane approximation and not by any means an accurate measure of DNA from ancestors.

SQL Graph offers some tools to play with this kind of data and perhaps arrive at some interesting conclusions for our personal database. Thanks for reading.

This month’s T-SQL Tuesday is hosted by my friend across the pond – Alex Yates. Alex has a fantastic topic for us to blog about – he asks us to talk about why we changed our mind, on anything related to our careers. What was our original opinion, why we believed that, and what we believe now.

I have many things to relate in this regard.  I decided to wite about two significant decisions, one technical and the other non technical. I am including both in the same blog post.

Technical point on which I’ve changed my mind: ORMs are evil.
In most shops I have worked at – ORMs or Object Relational Mappers such as NHibernate and Entity Framework have been a DBA’s nightmare. They used to generate horrific queries and the inability to control what is generated when made it incredibly hard to work with. Over time, I’ve worked closely with developers and understood (well somewhat) their need to use such things. I’ve learned how to streamline ORM usage so that it doesn’t become the evil nightmare that it can. To do that – I try to do the following:

1 Keep calls down to basic CRUD operations. This is essentially all that ORMS were designed to do. The queries doing basic CRUD are parameterized, not that evil.   
2 Avoid treating tables like objects and doing object-object mapping – relational tables are not objects.
3 Use stored procedures wherever possible or wherever ORM queries are nightmarish. The ORM can call the stored procedure.

With such basic rules in place, am able to manage ORM generated queries better. I don’t think I will ever love an ORM, but am down to thinking they are not as evil as we data people consider them to be.

Non technical point on which I’ve changed my mind: Career progress is a thing and is different from what makes me happy.
I believed this for a long time – that there was something wrong with sticking to a job you like, or not getting big pay hikes, or that your next job should be ‘bigger’ with more responsibilities than your earlier one, and on and on. I defined career progress in terms of all these things, and thought I need a roadmap to live by that said – in 5 years – I am here, in 10 years am here, and so on , each level being with a different job title and of course, more money. After several job changes I have found out – there is no such thing. There are only jobs where you are happy, or not happy at. And happiness may very well include money, and job titles , for some. For me, it is mostly about quality of work, and working with smart people. I do need money, we all do –as long as the job pays me decent money, gives me quality work to do, and a good team to do it with – there is not much else to go after. Life is short, being happy at what we are doing matters. Most of us spend atleast 8 hours a day at work, if not more. It is important to be happy there, doing what we enjoy doing and liking atleast some of the people we work with. Success is really nothing more than that. To me. I don’t complicate my mind trying to figure it out any further.

Those are the two things I’ve changed my mind on. Thanks Alex, for the great topic. I look forward to reading what other people in community have to say on this.

‘Shortest path’ is by far the most feature of SQL Graph for now. What does this even mean?

‘Shortest path’ is the term accorded to the shortest distance between any two points, referred to as nodes in graph databases. The algorithm that helps you find the shortest distance between node A and node B is called the Shortest Path Algorithm.

Let us go back to the movie database. We have two people, say Amrish Puri and Harrison Ford. Amrish wants to meet Harrison Ford. He has not acted with Ford, he may have a few connections in common – or people who know him. Or people who know him who know him. This is one way to get an introduction. Or, let us say you are interviewing for a job. You want to see if someone in your network works at that place – so that you can get an idea of what the job or the company is like. So you go on linkedin – do a search for the company, look under ‘people’, and it tells you if anyone in your network is there, or someone is 2 levels away, or 3. Those numbers are what we get from the shortest path feature.

Aside from social media examples, what are the specific uses for this feature? Below are a few ways you can put this to use –

1 Find the path to person you want access to from a large organizational chart
2 Find connections between specific tables in an ERDiagram (yes that is graph data too)
3 Find connection between two resources in a data center graph model
4 Find which store is closest to customer or various applications related to geography

You can even make a graph data model of characters in a complex novel and explore relationships that way.

And so on.

In this I will illustrate the examples of shortest path with the movie db:

Below illustrates connections from Harrison Ford to all other actors in the database

SELECT STRING_AGG(toActor.PersonName, '->') WITHIN GROUP (GRAPH PATH) AS FriendConnections,

          LAST_VALUE(toActor.PersonName) WITHIN GROUP (GRAPH PATH) AS FriendName,

          COUNT(toActor.PersonName) WITHIN GROUP (GRAPH PATH) AS levels

FROM

          PersonNode AS fromActor,

          CoActorLink FOR PATH AS f,

          PersonNode FOR PATH AS toActor

WHERE

               MATCH(SHORTEST_PATH((toActor<-(f)-)+fromActor))

               AND fromActor.PersonName = 'Harrison Ford'

The results show us how many levels away the person is as well, and who are the people on the path if they are more than one level away.

We can filter this of course to find only people who are only one hop away, or two levels away.

SELECT PersonName, Friends

FROM (

       SELECT

              Person1.Personname AS PersonName,

              STRING_AGG(Person2.Personname, '->') WITHIN GROUP (GRAPH PATH) AS Friends,

              COUNT(Person2.Personname) WITHIN GROUP (GRAPH PATH) AS levels

       FROM

              PersonNode AS Person1,

              CoActorLink FOR PATH AS fo,

              PersonNode FOR PATH  AS Person2

       WHERE MATCH(SHORTEST_PATH(Person1(-(fo)->Person2){1,3}))

       AND Person1.Personname = 'Harrison Ford'

) Q

WHERE Q.levels = 1

If we want connections between two specific people, we can do it as below.

SELECT PersonName, Friends, levels

FROM (

       SELECT

              Person1.Personname AS PersonName,

              STRING_AGG(Person2.Personname, ‘->’) WITHIN GROUP (GRAPH PATH) AS Friends,

              LAST_VALUE(Person2.Personname) WITHIN GROUP (GRAPH PATH) AS LastNode,

              COUNT(Person2.Personname) WITHIN GROUP (GRAPH PATH) AS levels

       FROM

       PersonNode AS Person1,

              CoActorLink FOR PATH AS fo,

              PersonNode FOR PATH  AS Person2

       WHERE MATCH(SHORTEST_PATH(Person1(-(fo)->Person2)+))

       AND Person1.Personname = ‘Harrison Ford’

) AS Q

WHERE Q.LastNode = ‘Tom Cruise’

In following posts I will explore more specific, every day examples of this.

In this post we saw how to create some graph tables with data. In this I will explore simple queries off of this data and how they compare with their relational counterparts.

The main goal behind a graph design is to help you answer queries – so what are the questions you’d ask of a movie database, if you had one? Mine would typically be like below.

1 Who are the actors in this movie?
2 Who is this movie directed by?
3 Who is the most prolific actor, according this dataset?
4 How many actors are also directors?
..and so on.
Lets answer these one by one, and see how they compare relationally. So if i were to answer the first question the typical relational way – my query would be as below:

SELECT c.actor_name from movies a, moviesactor b, actor c

WHERE a.MovieId = b.movieid AND b.actorid = c.ActorID

AND a.Movie_Title = 'Jurassic Park'

This is a very simple two table join – if we were to do the same with newly created graph tables – the query would look like below.

SELECT p.personname FROM dbo.personnode p, movienode m,moviesactorlink a

where MATCH(m-(a)->p) AND m.movietitle = 'Jurassic Park'

The queries for other questions, with their relational counterparts, are as below.

--Most prolific actor

SELECT TOP 10 c.actor_name,COUNT(1) AS moviesactedin from movies a, moviesactor b, actor c

WHERE a.MovieId = b.movieid AND b.actorid = c.ActorID GROUP BY c.actor_name ORDER BY moviesactedin desc

SELECT TOP 10 p.personname,count(1) AS moviesactedin FROM dbo.personnode p, movienode m,moviesactorlink a

where MATCH(m-(a)->p) GROUP BY p.personname ORDER BY moviesactedin desc

--2 Actors who are directors

SELECT c.actor_name,a.Movie_Title from movies a 

INNER JOIN moviesactor b

ON a.MovieId = b.movieid

INNER JOIN actor c 

ON b.actorid = c.ActorID

INNER JOIN MoviesDirector d

ON a.MovieId = d.movieid 

INNER JOIN director e ON

d.directorid = e.directorid

AND e.director_name = c.actor_name

SELECT p1.personname, m.movietitle FROM personnode p1, movienode m, moviesactorlink a,moviesdirectorlink d

WHERE MATCH(m-(d)->p1 AND m-(a)->p1) 

The advantages are
1 Fewer number of tables
2 Easy to write as opposed to a lot of joins.

The node table usually has a seek operator on it, but edge tables are scanned since it is not possible (currently) to create an index on edge id. I will explore the most useful part of this feature – shortest path, in the next post. Thanks for reading!

In the previous post on this we saw what is a basic graph data structure, and the layout of an example – a movie database with it. In this I am going to explain how to convert that design into graph tables.

The SQL Server graph architecture is explained really well here.
I already have some relational tables with data for this model.

My relational model looks like below.

Why is this a good example to convert into a graph data model? There are atleast two many to many relationships – moviesactor and moviesdirector. And if you consider making a table of who acted with whom – coactors, that would make it 3. Many to many relationships/bridge tables are a key indicator of what makes a good candidate for graph data. So we are past Step 1, identifying if the data is a good candidate. The next step is to list the questions we want this new model to answer. Mine may be as below:

1 Who are the actors in this movie?
2 Who is this movie directed by?
3 Who is the most prolific actor, according this dataset?
4 How many actors are also directors?
5 What is the shortest path/number of connections Person A needs to reach Person B? (A person may be an actor or a director).

..and so on. If we look at the nouns here – actors/directors – those make up a node. Movie, is another node. We can choose to make actors and directors separate nodes, or put them into one node, called person node. The only criteria here is how much that one table is going to get hit query wise. In this case, since it is a small dataset with minimal querying, I choose to go with one node, called Person Node.
The edges are the verbs – acted, directed and co starred. So each of them make up an edge table. My data model looks like below.

USE  MovieData_Demo;
 go

DROP TABLE IF EXISTS PersonNode;
   GO
   CREATE TABLE PersonNode (
     PersonID INT IDENTITY(1,1) NOT NULL    PRIMARY KEY,
     PersonName varchar(500)  ) AS NODE;

Now I get a node table..i’d like to see what the node table looks like.

sp_help 'PersonNode'

I have highlighted in red what SQL Server adds to the table – the two system columns – graph id, which is bigint, and node id, which is nvarchar and stores json, and the unique index to help with queries.
We can also see from constraint type that this table is similar to other relational tables – it can be enabled for replication and can have related delete or update actions defined on it if need be.

We can now insert data into this table from relational tables as below.

INSERT INTO PersonNode (PersonName) 
 SELECT actor_name FROM MovieData.dbo.Actor
 UNION 
 SELECT director_name FROM MovieData.dbo.Director

Selecting data from the table gives us below. It is interesting and informative to see how node id is stored as JSON.

SELECT * FROM PersonNode

We can create the movie node similarly, as below.

DROP TABLE IF EXISTS MovieNode;
 GO
 CREATE TABLE MovieNode (
     MovieID INT PRIMARY KEY,
     MovieTitle varchar(500) NOT NULL,
     MovieLanguage varchar(500) NULL,
     MovieCountry varchar(500) NULL,
     MovieFacebookLikes INT NULL
   ) AS NODE;

INSERT INTO MovieNode (movieid,movietitle,movielanguage,moviecountry,moviefacebooklikes) 

SELECT [MovieId],[Movie_Title],[Language],[Country],movie_facebook_likes FROM MovieData.[dbo].[movies]

Now that we have the two basic nodes, lets try and create the edges or connections between them.

DROP TABLE IF EXISTS MoviesActorLink;

  GO

  CREATE TABLE MoviesActorLink (

    Link BIT NOT NULL DEFAULT 0,

    MovieActorLevel smallint NULL,

    MovieActorFacebooklikes DECIMAL NULL,

    CONSTRAINT EDG_MoviesWithActor CONNECTION (MovieNode TO PersonNode)

  ) AS EDGE;

Let us explore what an edge table looks like under the covers.

sp_help 'MoviesActorLink'
 

As highlighted in the red square on top, there are a whole bunch of system columns added for an edge table – the first two, graph id and edge id are unique identifying columns while the rest are for the nodes we plan to connect using this edge. There is also a default index added on graph id.

I chose to add a constraint on two nodes i plan to connect – movie node and person node. In case anyone wants to delete data from either of the node tables – there should not be an orphaned record in the edge table that points to the deleted node. This constraint can come in very useful.

Now I am ready to insert data into the edge table from relational table. I do this as below.

INSERT INTO MoviesActorLink ($from_id, $to_id,movieactorlevel,movieactorfacebooklikes) 

 SELECT a.$node_id, p.$node_id,c.actor_level,c.actor_facebook_likes FROM dbo.MovieNode a

 INNER JOIN MovieData.dbo.MoviesActor c ON a.movieid = c.movieid

 INNER JOIN MovieData.dbo.Actor b ON c.actorid = b.actorid

 INNER JOIN dbo.PersonNode p ON b.actor_name = p.personname 

The data in my the newly created edge table can look as below.

SELECT * FROM dbo.MoviesActorLink

As we can see the node and edge ids are all json based pointing to existing nodes. In the next post I will explore running simple queries off of this data. Thanks for reading.

In part 1 of this interview we talked at length about what it took for Lashana to make it into tech, her recognition by the then President to a huge audience, and related. In the second part I asked her some questions regarding her advice for women in tech and various situations we have to handle.

Mala:         What advice would you have for young women of color or minorities who want to get started in tech? Or if you had to do it differently, how would that be? As a younger person?

Lashana:              I would tell myself, “You know more than you think you know.” I always went into any tech situation expecting that I had a lot to learn and it would be a really hard road and my knowledge level was really low. It’s like, a lot of it is about whether or not you have the spirit and the audacity to push forward even when you might not know the answer to something. Or when something gets difficult.

Mala: How does diversity add value to a technical team? In other words what advice would you have for companies to hire diverse people on their tech teams?

Lashana: What I found out is people who are good at troubleshooting are usually the people that I want on my team because I need you to think a different way about how to solve a problem than what I’m thinking. If I knew the answer I would not need any help and the problem wouldn’t exist right now. A lot of women and people of color and oppressed minorities in general have to find a different way to do something anyway – that makes them really good at out-of-the-box thinking. That is one reason why diverse teams can be so good at solving problems.

Their troubleshooting abilities are already there. Companies can bring that to the table and that is way worth more than what they actually think it is. A lot of technical stuff can be learned. Every job has to train you technically because every job has a slightly different version of whatever program that they’re using. I don’t think I’ve ever had one job in my 26 years of working jobs where I use the exact same version of a program from one job to another. I always had to retrain myself and it took three to six months sometimes before I could actually get to the level that the rest of the employees are.

<<I was really impressed by her line that women and people of color have to do it differently anyways. I have seen this validated multiple times. One of my ex bosses was once trying to pick someone on his team to do a presentation for senior management..he picked me over lot of better presenters because he thought I had the ‘best poker face’ while facing serious situations. Truth is am not poker faced at all. But I learned to be that way in some situations because I had to face immigration multiple times..and anyone who has done that knows you keep any kind of expressions or emotions at bay. I’ve also been at multiple places where women are considered good at multi tasking over men. We learn that by multi tasking at home – most of us have to.>>

Mala:       When does a person make a call to move on from a job/situation? This is something that I have found challenging myself. Sometimes you have to live it through things and speak up/try to change and sometimes you have to move on from a gig because you think you’re no longer going to be seen there? Obviously I need a job, I will keep going. Every place I go, I encounter the same kind of stereotyping and bias and all of that.

Lashana:              I faced that challenge as well. I always tell people, “Look, I don’t know what your parents’ situation is. If you have kids to feed and other things to take care of. I don’t want to be that person telling you to leave the job and then you’re stuck financially.” But for those that can do a little bit more, there have been suggestions to make stealth job searches. If you can do that, that’s great. There are recruiters that will keep your information secret and they’ll make sure that the employer that you’re with right now doesn’t know that you’re job searching. But for me, when I knew that I needed to leave, and I tell this to everyone, it’s like, “You already probably should been left three to six months before you actually, you did.”

Mala:                     Right, I felt that all the time.

Lashana:              Yeah. It’s always going to be scary. Instead of expecting it to be like, “Oh, I’ll leave when it feels right and everything’s settled down” … It’s always going to be scary because nobody wants to leave a place that they literally spent most of their waking hour at for most of the week. You’re adjusted to it. You know where you sit, you know what the temperature of the room is, you know all the good spots to eat and all of that stuff. Nobody wants to leave the comfort zone. You have to get over the expectation for it to feel okay. The line to remember though to start that process is ‘If you are not being respected, it’s not you.‘It’s not, “Keep your head down.” It’s not, “Don’t ruffle the waters.” If you’re not being respected as an adult, then you need to make whatever plans you need to make to leave. I think that’s the one thing that I try to get through is that people feel like, “Well, maybe I’m just being pessimistic. Or maybe I’m just being too picky.” I’m like, “No, you’re basically saying that you need to be respected. If they’re not respecting you, then yes, that’s not a place for you.” How soon you leave depends on other variables, but it’s not you. You’re not going crazy. You’re not imagining things, it is happening.

<<Am not sure I can think of a better/simpler bottomline to make the decision to leave. Lack of Respect. And remembering that it is not me, or that it is okay because am used to it. The line to get out of our comfort zones is invaluable, I could hear it any number of times.>>

Mala:                     So I think that’s all I had on my list of questions. Would you have any questions for me regarding PASS, regarding anything else?

Lashana:              I know that PASS is nationwide. I’m guessing it’s also international?

Mala:                     Yeah, we are an international data community. We started nationwide, but right now we’re across 58 countries. The conference that you’re going to be at has attendees from around 35-40 different countries in the world.

Lashana:              Oh wow.

Mala:                     Yes. We have user groups/chapters, we also have special interest groups. One of them is the Women-in-technology group – headed up by Kathi Kellenberger (who reached out to you), and Rie Irish. Rie and Kathi also set up the women-in-technology happy hour and the lunch hour where you’re going to be speaking at. We also usually have an LGBT happy hour, karaoke parties (which was also started by Kathi several years ago) and many parties thrown by vendors in the evenings. It’s a lot of fun. Its our year 21 this year. Almost like a family reunion for so many of us since we’ve been part of it for a very long time. We love to show it off to new people and most I’ve known feel very much at home. It is a really unique community, lots of very caring people.

Lashana:              Oh wow. So yes, that’s fantastic. Every time I run across someone that’s, and it’s mostly database professionals, am I correct?

Mala:       Yes, we started with database people around Microsoft SQL Server, so the original expansion of acronym PASS was Professional Association of SQL Server. But right now, because of the way the industry itself has changed, they’ve gotten away from that association and haven’t come up with a very good alternate name yet. We still are PASS by most of us. We are people who primarily work on the Microsoft data platform that is also expanding into other database technologies as well as open source.

Lashana:              Oh, okay. Awesome. But yes, I tell any database professional that I meet. I actually, and this may be something for a later time, but there is a black women’s tech summit that’s starting to formulate in Philadelphia.

It’s called HUE, H-U-E. It is black women and women of color that are somewhere within the tech realm. They’re in their second year. I got to them in the second year and I actually went to the conference. They asked me to speak on a panel about being a woman in tech and how that is. But they’re growing. So if it’s something that PASS maybe wants to put on their radar as it grows, it’s a fantastic opportunity. They ended up getting some really big sponsors for the second year. So the only thing I can see is that it’s just going to keep growing.

Mala:                     That’s awesome.

Lashana:              I had never been in a conference with literally 200 women of color, all in tech.

Mala:                     Oh wow. You’re allowed to attend even as a non black person? Like a brown person and such?

Lashana:              Absolutely.

Mala:                     Oh cool. Yeah, I would definitely keep it on my calendar. So is it about database technology? Is it about any kind of tech?

Lashana:              Any kind of tech. So you’ve got some cybersecurity people, you’ve got some SQL database people. Because I actually ran into someone who works in databases and I told her about PASS and she said, “I’ve never heard of it.” I said, “You have to check them out.” So I went on ahead and gave her the link and told her that I would be at the summit. But yeah, she was super interested in it because she said as a woman in tech that works with databases, she doesn’t really have a group. I said, “The women in technology group is virtual from what I understand, so it doesn’t matter where you are. You can just join in and have other women to talk to.” So hopefully she did go ahead and sign up. She sounded really excited about it. But I was just thinking that could be a great platform.

Mala:                     If you have flyers or anything like that, I’d be happy to promote it among our community.

Lashana:              Absolutely. I will absolutely do that. Let’s see, I’m trying to think if I have any other questions. I think that’s it. Thanks you much for this conversation. This was awesome.

Mala:                     Yeah. Same here. Thank you. I appreciate it.

Thank you Lashana, for your time and many valuable insights.
We really look forward to having you at PASS and introducing our great community to you.

Readers – Lashana Lewis can be reached on twitter here and her linkedin profile is here

Thanks to PASS for helping me set this up and to everyone for reading!!

I have been impressed by profiles of women invited to the annual Women-in-Technology luncheon at the PASS summit in the recent past. When the announcement comes out, I normally look up who the person is and read about them. When PASS offered an opportunity, as an official blogger at the summit this year – to interview Lashana Lewis, this year’s invitee to the WIT session at the summit – I jumped at the chance.

I must state here that I am really not that easily overwhelmed by many challenges people have at work, especially women, in this country. I try to be kind and compassionate whenever I can – but many problems are pale in comparison to what I have been through personally, coming from a highly patriarchal society in a third world country. But Lashana’s story and her character that came through were bright as a diamond even to me – so much that the term that came to mind was the sanskrit word ‘Vajrasara’, which essentially means ‘strong and bright as a diamond’.

Below is my interview with her. This was fairly long – I’ve made it into a two part blog post – the first part talks of her history and how she got here, and the second part is advice related to diversity,survival as a woman of color in tech and so on. I considered uploading the audio first for people to listen – but there are so many links to other things and valuable information in here – plus it flows better as a story if I write it.

Mala:         Can you go give me a brief history of how you got here?

Lashana:     Sure. I’m actually, to some folks’s surprise, a tech geek for a really long time – ever since I was a kid. My favorite story as a kid is that my mother would have me take apart things and put things back together. I was a curious kid. One day I wanted to take apart a brooch that she received from her mother from a long time ago. She said “Don’t mess with that. I know you want to fix it but don’t mess with it. We’ll make an agreement of what you can and can’t take apart and try to fix.” She would allow me to break the toaster apart and put it back together. That was our agreement – I had to ask her for permission before taking things apart.

I learned from that – the things that get you in trouble are the things that you end up being really good at.

Mala:                     Yeah. that is so true.

Lashana:              Yeah. I had a chance to purchase a computer through a program that I was a part of in high school. When that broke I went and I found parts, put it together and repaired it. My teacher saw that I was really good with not only that, but also computer programming. So he suggested that I go into computer science. So I went to Michigan tech university for about three and a half years on a scholarship for minorities in engineering. I had some trouble. I faced some issues then. There were probably a handful of people of color. Two people were Indian.

It was me and them the rest of them were white guys. So basically we just had a really tough time trying to get through and even get through some of the curriculum. I ended up leaving after three and a half years because of two things. One, because of that toughness, but two, because I ran out of scholarship money. Back then the Pell Grant didn’t pay for summer and I went to school 17 hours away from my home and I grew up in the projects of East St Louis, Illinois – which is an economically deprived area. I didn’t have the money to keep going back and forth.

I stayed there for literally three and a half consecutive years. Then I came home and tried to find a job. I couldn’t find one in spite of the fact that I had programming skills and most of the things people were asking for were data entry and very basic things. I was a computer lab assistant when I was in college. What they were asking me to do was very easy. I was even designing websites, and this is back in 1998 before the internet was this thing that everybody had. So couldn’t find a job. I became a van driver for an after school program. That was the only job I could find. I did that for about six years.

<<Lots of us do various other jobs before ending up in IT. But that is somewhat different from being fully qualified for an IT job and not being able to get one. In my time the only people who landed IT jobs were those who went to school for an engineering degree – so my first job was doing data processing and various miscellaneous tasks at a textile shop that almost cost me a lung because of the pollution. But she had to drive a bus for six years before she even found something in IT. I was mind boggled to hear that>>.

Lashana:              Yeah. I did that for about six years. In the meantime I made friends with all the IT guys. I was able to help during the whole 2000, Y2K bug thing when everybody was freaking out. I was able to update the bios for different machines. I just kept my skills up. But at the same time I still wanted to not do these side jobs after the van driving, I was a customer service agent – I could never get into tech.

I had an opportunity at one of the places I was working, which was a university, to take some classes and refresh some of my knowledge for free. So in the middle of two programming classes both professors didn’t even really know each other that much, but they both gave me the same suggestion to be a part of this program called LaunchCode. It was very new. Not many people had heard of it. It wasn’t even a year old yet. I ignored them. Then I literally sat myself down and said, “Your teachers are telling you to go to this program, to stop doing what you’re doing now. Finish your class but go to this program.” I ended up going. I hadn’t finished my degree at that time. I had the opportunity to do it for free – but they were urging me to do this Launch Code program, so I did it.

I started in June of 2014 right after school had ended for that semester. By August of 2014 I had an interview because basically one of the facilitators with LaunchCode saw that I knew how to program already and she said, “Well, do you need help with anything?” I said, “No, I just can’t find a job in IT.” She set me up with an interview. I drove out to MasterCard, which is right here in O’Fallon, Missouri, maybe about 40 minutes outside of St Louis .I interviewed and was hired that next month. In September I started my apprenticeship. Usually it’s a three month apprenticeship. One day my boss brought me to the side – I thought I was in trouble and he said, “No, no, no. I want to hire you full time. “

He gave me my first real IT job and by November I was a full time employee at MasterCard. I was a systems engineer. I worked with the Windows team. I trained another team in Chennai, India. Then from there I ended up switching over to software engineering so I could actually use the programming skills that I had to learn 10 years previously. I used those for about six months. A lot of people were bringing me in because one of the cool things that happened because I went through the launch code program . I was doing so well that it caught the eye of Barack Obama, the president at the time.

Mala:                     I saw how that picture on your twitter profile and I was like, “Oh my God, isn’t that cool?!”

Lashana:              It is cool. LaunchCode was trying to get some testimonial videos because it was very early program and they were trying to get people interested. It was a hot sweaty day – I stood in front of a camera and just blabbed for about 10 minutes. Then they filmed me in a couple of other places talking. Barack Obama got his eyes on it . Him and his economic policy advisor at the time – Byron Auguste, got together a program that would basically make grant money available to do other programs like Launch Code all across the nation. It was a $100 million grant opportunity for all of these different programs. Whenever the President announced these things, he tried to bring people related to the events. He asked me if I would come, through his assistants. It wasn’t him calling me up. I would’ve probably passed out. But he asked his assistants to come and contact me and get everything together. I went out to Washington DC and I sat and I listened to him talk about me. It just so happened that right when he was getting ready to do his speech, I was able to text my mother and tell her to turn on CSPAN and she said, “Okay.” At that moment my phone died. So I didn’t know what happened until after the whole entire thing. I finally got back to my hotel room, charged the phone and called home – my sister answered and I asked, “Where’s mom?” And she was like, “Don’t start talking again. Mom just stopped crying. She’s been watching this.”

Mala:                     That’s such a story, oh my God. Yeah.

Lashana:              “She’s been crying for like the last five hours so no, just stop.” I was like, “I didn’t do anything.” But yeah, that was a great thing. Obviously I took a picture with him. right after he gave the speech, which was fantastic. Because of all of that highlighting and because I was out there, people were like, “Well you have all these skills, why did it take you so long to get into the tech field? Didn’t you just go and apply?” I’m like, “Yes, of course I applied. I applied, I talked to people, I tried to make friends with people. It did’nt work – there was always something in the way.

<< I grabbed a bunch of tissues after this. It is an incredible moment when your loved ones get to see you succeeding. Also, the incredulousness people displayed when she explained how long it took for her to make it really struck a cord with me. I am faced with a lot of this on various fronts – starting from my personal life to various aspects. I try hard not to pose this kind of questions to people. Life is different depending on many things…never assume the opportunities you have in any regard are available to everyone else. Never take anything you have for granted>>.

Lashana:        I ended up talking a lot about diversity in tech and what the issues were for, particularly black women, getting into tech. But minorities in general. So from then I had two lives. In one life I was this IT engineer doing systems engineering and software engineering – I am behind a desk and not really talking to many people. Then suddenly I was called out to Washington DC to be interviewed by Tom Friedman of the New York Times to talk about what my life was like trying to get into IT. That got me into the more granular things, statistically and data wise – why is this happening? What is actually keeping people from having more women of color or people of color in general into these fields?

I started putting together some slides and I did one presentation at a conference called Lesbians Who Tech. During that presentation I talked about the digital divide. I talked about the racial dot map that’s out there, which a lot of people don’t know about. It’s basically a colored dot map for every person that responded on the US census. It actually is colorized depending on what ethnicity you identified as. It’s put onto a Google map so you can literally look anywhere in the United States and see what the racial density is of different areas. So I was starting to collect more and more information like that. So when I put together the presentation for data-driven diversity for pass wit, it really got me to looking at the statistics and trying to figure out and wonder why people weren’t aware of some of this information and how they could use it to make changes within their own company.

What I really got out of this part of the interview – in addition to personal inspiration from one woman of color to another – is how LaunchCode helped Lashana succeed. To me a lot of my visibility and success can be similarly attributed to my volunteering efforts with PASS – it gave me a platform to contribute something and to be seen as someone more than just a techie working a job, like so many others are. These associations matter and can work in very beneficial ways.

In the next part I will be discussing with Lashana on the importance of diversity in tech, hiring strategies, when to stay and when to leave decisions and so on..stay tuned..and thanks for reading!!