How To Build and Lead a Winning Data TeamCahyo ListyantoHead of Data Analytics Bizzy IndonesiaJakarta | August 2017

Business OverviewThe PillarWinning Data Team

Infrastructure

Product

People

Business OverviewBuilding Data Team

Ask yourself:• What data will your teams be working with?• What do you want to do with this data?• Who is going to benefit from this data’s generated value? Directly (ie. the user or consumer of the generated value);

Indirectly (ie. the organization’s bottom line)• How much time and money can you invest in this project?• What ROI do you expect?

Hiring Intelligently• Identify your team’s existing skill sets and what you might be missing• Prioritize according to immediate needs• Include analysts in your data science team

Technology ,Tools & Resources to Achieve the Goals• Think about scalability• Think about accessibility & stability• Think about the tools• Buy / Rent / Build

Business OverviewThe Importance of Soft SkillsBuilding Data Team

Get To Know The Problem• Understanding what actually must be solved• Never be analyst to whom problems are “throw over the fence”• The problem you’re asked to solve is often not the problem that needs solving• Solve the correct, yet often misrepresented problem

Learn How to Communicate• Without the ability to communicate, it becomes difficult to understand others challenges, articulate what’s possible, and

explain the work you’re doing• Practice makes perfect.

Key Attribute for Data Personnel:• Independent• Questioning• Innovative• Adaptive• Intuitive• Mentoring

Business OverviewBuilding Data TeamThe Trend

Business OverviewThe UnicornBuilding Data Team

Business OverviewTime Consumption and The Least EnjoyableBuilding Data Team

Business OverviewTeam Components & SpecializationBuilding Data Team

Data Engineer:• Data Collection• Data Warehouse Modelling• Data Transformation

Data Analyst:• Data Exploration• Data Visualization & Presentation• Business Knowledge

Data Scientist• Machine Learning• Statistics!• Insight Seeker

Data Ops• Big Data Infrastructure• Data Architect• Data Security• Data Performance

Data Steward• Master Data Management• Data Cleansing• Data Catalog

Business OverviewSolution ComponentsData Infrastructure

Analysis ServicesTabular

WebScrapper

DataSource

InformationManagement

MasterDataServices(MDS)

DataQualityServices(DQS)

IntegrationServices(SSIS)

Cleanse

Manage

Integrate

DataStorage

DataModelling

DataWarehouse

DataVisualization

NotDevelopedYet.Areaforfuture/plannedimprovementsNote:

IdentityManagement

AzureADConnect/Sync

NotPlannedYet

Analysis ServicesMultidimensional

Excel

Ad-HocReport

InternalDashboard&MobileBI

InternalReportingPortal

ReportingServices(SSRS)

DataScience

AzureMachineLearning

BackOfficeApps

Deprecated.MigratedtoSQLServerMasterDataServices(MDS)

DataStaging

SQLDatabase

External/CustomerDashboard

PowerBIEmbeddedForBizzySELECT

ExternalInteraction

AzureFunction

DataLake

AzureCognitiveServices

Business OverviewSolution Architecture - Data WarehouseData Infrastructure

BackOfficeApps

LOBApps

WebScrapper

ExternalDataScrapper

MasterDataServices(MDS)

DataInput&Management

DataPreparation

IntegrationServices(SSIS)

DataQualityServices(DQS)

DataStaging

SQLDatabase

DataWarehouse

Analysis ServicesTabular

DataWarehouse

OLAP/Cube

Consume

Excel

ReportingServices(SSRS)

ExecutiveDashboard

Business OverviewInfrastructure Cheat SheetData Infrastructure

Size Big Small

DataType UptimeGrowth Slow Fast Fast Slow

StructuredHigh OnPremDB/DWH CloudDB/DWH OnPremDB/DWH

Low CloudDB/DWH CloudDB/DWH

UnstructuredHigh OnPremHDPCluster

Low Ad-HocCloudHDPCluster

ex.Products

OnPremDB/DWH SQLServer,Oracle,Postgre,MySQL

OnPremHDPCluster Cloudera,Hortonworks,MapR

CloudDB/DWH AzureSQLDB,AzureSQLDW,AWSRedShift,GCPBigQuery

Ad-HocCloudHDPCluster AzureHDInsight,AWSEMR

Business OverviewData Jujitsu by Dr. DJ Patil - Turning data into productData Product

When in doubt, use humans

Start Simpleembraces the notion of the minimum viable product and the simplest thing that could possibly work

Ask yourself:

1. What do you want the user to take away from this product?

2. What action do you want the user to take because of the product?

3. How should the user feel during and after using your product?

Business OverviewDrive Action with Data in BizzyData Product TIPS!

Customer SO

Finance Approval

Buyer Create PO

GRWarehouse

Shipment

Cust Received

DO Collection

Finance Invoice

Customer Payment /

AR

Vendor Payment /

AP

B2B e-CommerceDaily Notification of end to end processInternal Notification• Finance Pending Approval• Buyer Pending PO(Back Order)• Vendor Pending GR• Pending Shipment• Pending DO Collection• Finance Pending Invoice• Vendor Pending Payment• Customer Pending Payment• Etc

External Notification• Customer AR Statement• Vendor Payment Information

Business OverviewDrive Action with Data in BizzyData Product TIPS!

Daily Notification of end to end processSample Report Layout

99 AVG $

Summary/Statistics

Category 1

Category 2

Category 3

Category 4

Series 1 Series 2 Series 3 Series 1 Series 2 Series 3

99 MAX $

a b c d e f g h i f2 g3

Trend of work performance

Detail Pending Item need follow up

Business OverviewBizzy is Hiring!!!Join Winning Tech Team

- Software Engineer - Front End- Software Engineer - Back End/Full Stack- QA Engineer- UI/UX Designer- Tech Writer

Some of our stack: PHP, Laravel, Javascript, vue.js, node.js, MySql/MariaDB, MongoDB,AWS (Lambda, EC2, RDS, S3, SNS, etc)Selenium, Postman, JIRA, Bicbucket, Confluence, Pipeline, etc