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ricklentz / new_analyst_excel_onboarding.txt
Created June 19, 2017 13:16
Excel onboarding for new analysts
Sort and filter data
https://support.office.com/en-us/article/Sort-and-filter-data-ffb9fcb0-b9cb-48bf-a15c-8bec9fd3a472?ui=en-US&rs=en-US&ad=US
VLOOKUP: When and how to use it
https://support.office.com/en-us/article/VLOOKUP-When-and-how-to-use-it-9a86157a-5542-4148-a536-724823014785?ui=en-US&rs=en-US&ad=US
Use conditional formatting
https://support.office.com/en-us/article/Use-conditional-formatting-03ab07da-1564-4913-b69f-2b1a370c8910?ui=en-US&rs=en-US&ad=US
Take conditional formatting to the next level
real advantage comes from unique data
observations:
teams that start with a simple model but augment beyond inituial scope tend to perform best
secondary sources have proven invaluable in deriving insights E.g. Recorded future, entity tagging over time, delta analysis
git clone https://github.com/ZerBea/hcxtools
sudo apt install libpcap-dev libssl-dev libcurl4-openssl-dev
make
make install
Higher leverage activities instead of focusing on grunt work
best minds in the world to focus on the issue (IP development) access to top 3-5 winning solutions
Go on to hire them or continue on in consulting engagement
Branding, recruiting
leverage distribution
XGBoost library - part of 50% of winning solutions
Leaderboard forces question, why are these submissions above me better?
Anyone can sign up - no corrolation with winners and domain export knowledge (shared passion is for data)
Deep learning extended beyond computer vision problem
@ricklentz
ricklentz / sql_process_characterization.sql
Created July 10, 2017 15:42
Characterize SQL SERVER (offending) processes for targeting will KILL {PID}
-- Characterize offending processes for targeting will KILL (pid)
Declare @T Table (SPID INT,
Status VARCHAR(1000) NULL,
Login SYSNAME NULL,
HostName SYSNAME NULL,
BlkBy SYSNAME NULL,
DBName SYSNAME NULL,
Command VARCHAR(1000) NULL,
CPUTime INT NULL,
DiskIO INT NULL,
/*==============================================================================
Question 1: full transaction data for suppliers from Madison
and consumers from Stevens point and transaction value > 10
==============================================================================*/
SELECT s.Name "Supplier Name" -- list full transaction data
import os
import sys
from slackclient import SlackClient
def send_message_to_channel(message='hello, I did not override the message',channel='#systems'):
slack_token = "xoxp-12345"
sc = SlackClient(slack_token)
sc.api_call(
"chat.postMessage",
import os
import sys
from twilio.rest import Client
def send_sms(to_number='19005551212',message='the job is done'):
account_sid = "abc123"
auth_token = "12345"
client = Client(account_sid, auth_token)
message = client.api.account.messages.create(to=to_number,from_="+19005551212",body=message)
@ricklentz
ricklentz / group_by_examples.sql
Created July 16, 2017 02:00
a few group by example queries...
USE [DS715-Rick-Lentz]
--1 Product categories and number of products in each category?
SELECT Product_Category AS 'PROD CATEGORIES',
COUNT(Prod_ID) AS 'NUM PROD IN CATEGORY'
FROM Tb_Product
GROUP BY (Product_Category)
--2 Cities having at least 5 different consumers?
SELECT City
FROM Tb_Consumer GROUP BY City