ENTERPRISE DATA INTELLIGENCE Let’s Get...
Transcript of ENTERPRISE DATA INTELLIGENCE Let’s Get...
© 2016 ASG Technologies Group, Inc.All rights reserved
ENTERPRISE DATA INTELLIGENCE
Let’s Get Serious
SCOTT SNIVELYStrategic Sales Specialist, Data [email protected]
May 15, 2017
© 2016 ASG Technologies Group, Inc.All rights reserved
ASG Technologies
Why Should We Care About Data Intelligence
Business and Technical Data Governance
What is an Enterprise Data Intelligence Solution - Demonstration
Q&A
AGENDA
© 2016 ASG Technologies Group, Inc.All rights reserved
ASG TECHNOLOGIES - WHO WE ARE
ASG Technologies brings peace of mind to every enterprise with information access, management and control from legacy to leading edge environments.
PEOPLE
ANNUAL REVENUE INVESTORS
COUNTRIES
70%OF FORTUNE 500 COMPANIES
RUN ON ASG SOLUTIONS
Information overload and complexity of dataare slowing business decisions.
Volume Is Growing
Compliance Demands Broader and Deeper
Complexity of DataIs Increasing
© 2016 ASG Technologies Group, Inc.All rights reserved
• Large, Multi-Billion Dollar Retail Organization does not separate In-Store Sales from
On-Line Sales
• Mid-Size University has three different full-time student counts on website – low to high
count – 213 students @ $20,000 in revenue per student…$4,260,000 !!!!
• Large Hi-Tech firm has multiple Business Intelligence tools employed in different but
related departments, cannot agree on numbers. (SAP Hana, Tableau, Spreadsheets,
etc.)
WHY SHOULD WE CARE ABOUT DATA INTELLIGENCE
© 2016 ASG Technologies Group, Inc.All rights reserved
BUILDING THE CASE FOR ENTERPRISE DATA INTELLIGENCE
1 | Avoid Negative Corporate Impacta. PII Information b. $7 Million Average Data Breach
2 | Reduce Direct Costsa. Spreadsheet & DB Metadatab. Impact Analysisc. Saving 2/3 time = $150,000 / Year
3 | Efficient Audit Processa. Streamlined Audit Processb. Saving 10% of Audit Process Costs
4 | Tribal Knowledgea. Critical Data Element Changes Documentationb. 75% Savings on Learning Curve for
Stewards & SME
5 | Data Driven Decisionsa. 1% Positive Revenue Impact
6 | Lineage & Self Servicea. 10% Savings of Effort of Business
Users
“REGULATORY PRESSURE MAP…” EVOLVING BANKING REGULATIONS
KPMG PAPER ON EVOLVING BANKING REGULATION - REGULATORY PRESSURE INDEX
It been reported:
$100B fines to US banks since 20081
Financial firms are “too big to manage1”
Regulatory pressure and ability to deal with
them are in a varying degrees of maturity
across the regions 2
A key to sustainable risk governance is
developing, attracting, and retaining talent3
With above as the backdrop:
How should global financial firms
orchestrate Data Governance initiatives?
How to prioritize technology initiative in
alignment with regulations? – “what’s the
organizations core technology capability”
What is the pathway to developing,
attracting and retaining key IT talent?
© 2016 ASG Technologies Group, Inc.All rights reserved
CONVERGENCE OF BUSINESS AND ITSimilar evolving challenges and needs
• Policies
• Standards
• Business Rules
• Business Events
• Key Business Elements
• Critical Data Elements
• Reference Data
• ETL Rules
• BDL
• BI Reports
• Source of Record
• Data Profiling Metrics
BUSINESS I.T.
Operationalizing Data Governance
An equal, an unfolding business/IT collaboration process…
© 2016 ASG Technologies Group, Inc.All rights reserved
Applications
ETL
Reports
Databases
DW
Metadata Repository
Models
Sales
BusinessAnalyst
ITArchitect
FinancialController
ASG DATA INTELLIGENCE
• Keeping Business and I.T. on the Same Page
Ext Docs, URLs, etc.
VP of Finance
Dir of Acctg / Compliance
QualityMgr
GovernanceMgr
IT Architect
Metadata/Code Repository
Reports
Databases
DW
Invites active participation across business and IT communities…while still providing control / governance over change.
Governance Process
Zero Gap Data Lineage
ZERO GAPDATA LINEAGE
LINEAGEANYWHERE
DATA GOVERNANCE
LOB /LIFECYCLE
+
© 2016 ASG Technologies Group, Inc.All rights reserved
MINING FOR ENTERPRISE DATA INTELLIGENCEMore than 220 “out of the box” interfaces
Databases (11)
• DB2/zOS; UD
• Greenplum
• IMS/DB
• IDMS (f)
• MS SQL Server
• MySQL
• Netezza (f)
• Oracle
• SAS Data Set (f)
• Sybase ASE
• Teradata
ETL (12)
• DataStage
• DB2 Stored Proc (d)
• Informatica PowerCenter
• MS SSIS
• Oracle PL/SQL
• Oracle
• Data Integrator (f)
• Data Warehouse Builder
• Golden Gate (f, d)
• SAP
• BODI (f)
• Data Services (f, r)
• SAS
• Data Integration (d)
• Teradata BTEQ/SQL
Business Intelligence (13)
• Cognos
• Essbase (f)
• Hyperion (f,r)
• IBI WebFocus (f,d)
• MicroStrategy
• MS SSAS
• MS SSRS
• SAP
• Business Objects
• Crystal Reports
• SAS BI (f)
• OBIEE (f)
• QlikView (f, r)
• Tableau
Enterprise Architecture (18)
• SAG Predict <->
• ARIS Toolset <->
• Borland
• CaliberRM (f)
• Together Control/Center <->
• Casewise Corporate Modeler <->
• COOL:Biz <->; COOL:gen <->
• PowerDesigner <->
• ER/Studio <->
• ERwin <->
• Rational
• Data Architect <->
• Software Modeler (RSM) <->
• Software Architect (RSA) <->
• System Architect <->
• Systems Developer <->
• Rose <->
• Rational Rose XDE <->
• mictroTool case/4/0 <->LEGEND: <-> – Bi-Directional Interface; (f) – Field Developed Interface; (d) – In Development ; (r) – In Research
© 2016 ASG Technologies Group, Inc.All rights reserved
ERP (7)
• e-Business Suite
• PeopleSoft
• JD Edwards
• SAP
• SAP
• BW
• HANA
• Siebel
Big Data (7)
• Hadoop
• Falcon
• Flume
• Hive/HCatalog
• HiveQL
• Cloudera Navigator
• HDFS
• Sqoop
Other (5)
• CSV
• MS Excel (f)
• XML
• SAP BOMM (f)
• Trillium DQ tool
LEGEND: <-> – Bi-Directional Interface; (f) – Field Developed Interface; (d) – In Development ; (r) – In Research
Reference Data (6)
Unique Value Scanner
• Oracle• SQL• Teradata• Sybase• Db2• DB2 UDB
MINING FOR ENTERPRISE DATA INTELLIGENCEMore than 220 “out of the box” interfaces
© 2016 ASG Technologies Group, Inc.All rights reserved
MINING FOR ENTERPRISE DATA INTELLIGENCEMore than 220 “out of the box” interfaces
Distrib. Technologies (27)
•Microfocus COBOL
•CORBA® IDL
•Dynamic SQL
•Hibernate
•HP Vugen
• iBATIS (MyBATIS)
•Java ™
•JAXB
•JAX-WS
•JDO
•JPA (d)
•JSF (d)
•JSP
•J2EE Packaging
•MQ Series®
•Perl
•PHP
•SAP ABAP
•SAP Dictionary
•Spring Beans
•SQLJ
•Struts/Tiles
•Unix Shell Script
•Web Services (WSDL)
•XML
•XML Schema (XSD)
•XSLT
Microsoft Technologies (20)
•MS Access Schema
•MS Access Application
•ADO.Net Entity Framework
•ASP
•ASP.NET
•BizTalk/Messaging
•BizTalk/Orchestration
•C#
•C/C++
•LINQ.Net
•MS-DOS Shell
•NHibernate
•Pro*C
•SQL Server Schema
•SQL Server SQL Script
•SQL Server Stored Proc (T-SQL)
•Visual Basic
•Visual Basic.NET
•Windows Catalog
•Windows Communication Foundation (WCF)
Distributed Databases (16)
•DB2 UDB Schema Distributed
•DB2 UDB SQL Script
•DB2 UDB Stored Proc Distributed
•Informix Schema
•JDBC/ODBC Schema
•MySQL Schema
•Oracle® Schema
•Oracle® SQL Script
•Oracle® Stored Proc (PL/SQL)
•Sybase Schema
•Sybase Stored Proc
•Teradata Schema
•Teradata SQL Script
•Teradata Stored Procedure (SPL)
•HP Vertica Schema
•HP Vertica SQL Scripts
Distributed Schedules (6)
•ASG–Zena ™
•CA-Autosys (Workload Automation AE)
•CA–Unicenter TNG Workload®
•CONTROL-M® Distributed
•Cron
•TWS Distributed
Distributed SCM (11)
•Borland® StarTeam®
•CA-SCM
•CVS
• Git (d)
•Rational® ClearCase®
•Rational® Team Concert (RTC)
•SAP
•Serena® Dimensions® CM
•Subversion® SVN
•Team Foundation Version Control (TFS)
•Visual Source Safe® (VSS)
ETL (3)
•DataStage
•MS SSIS
•Informatica
© 2016 ASG Technologies Group, Inc.All rights reserved
MINING FOR ENTERPRISE DATA INTELLIGENCEMore than 220 “out of the box” interfaces
z/OS Technologies (29)
•APS
•Assembler z/OS
•BMS z/OS
•CA–ADS/O
•CA–Easytrieve® z/OS
•CA–Fast Unload for DB2 z/OS
•CA–IDEAL
•CA–IDMS/DC
•CA–Telon® z/OS
•CICS® z/OS
•CICSPLEX® SM
•CICS Application File Control (CAFC)
•COBOL z/OS (Cobol Enterprise 5.2)
•DELINK
•FORTRAN
• IMS/DC
•JCL z/OS
•MANTIS® z/OS
•Menu Support
•MFS z/OS
•MQ Series®
•NATURAL z/OS
•ObjectStar
•PL/1
•REXX z/OS
•SAS Base z/OS
•SMF z/OS
•SMP/E z/OS
•z/OS Catalog
z/OS SCM (6)
•ASG–LCM ™
•CA–Endevor®
•CA–Librarian®
•CA–Panvalet®
•IBM SCLM z/OS
•Serena ChangeMan®
z/OS Databases z/OS (10)
•ADABAS
•CA–DATACOMM
•CA–IDMS/DB
•DB2 Schema z/OS
•DB2 Stored Proc z/OS
•IMS/DB (DL/1)
•Model 204
•QMF z/OS
•SPITAB z/OS
•Teradata z/OS
z/OS Schedulers (9)
•ASG–Zeke ™
•ASG –Cortex
•CA-ESP z/OS
•CA–Jobtrac z/OS
•CA–Scheduler® z/OS
•CA–7® z/OS
•CONTROL–M® z/OS
•HS5000/APM z/OS
•OPC – TWS z/OS
iSeries (7)
• AS/400 Catalog
• AS/400 COBOL
• AS/400 Command Language (CL)
• AS/400 RPG
• AS/400 DB2 UDB Schema
• AS/400 DB2 UDB Stored Proc
• AS/400 Library File System
223
General Data Protection Regulation (GDPR)
A “Risk Based” Approach
Increased Penalties
DPO – Data Protection Officer
Focus on Quality and Governance
Principles Driven
Risks and Penalty Mitigation
The General Data Protection Regulation is a Regulation by which the European Commissionintends to strengthen and unify data protection for individuals within the European Union (EU). It also addresses export of personal data outside the EU.
The Commission's primary objectives of the GDPR are to give citizens back the control of their personal data and to simplify the regulatory environment for international business by unifying the regulation within the EU.GDPR has put in place substantial fines as an incentive for compliance.
Major Considerations
• Organization Readiness• 72 Hour turnaround time for data breaches• Fast-tracked application – May, 2018
Illustrative: for discussion
General Data Protection Regulation (GDPR)
Context Compliance GDPR Anti-Trust Sarbanes Oxley CCAR/KYC/BCBS 239 State International
Data Intelligence Structure to inform Business Community Guidelines for Developers
Business Rule to ensure in Compliance
Processes to be in Compliance
Standard Right to Forget Right to Understand Right to be informed
(Hacking) Right to Data Protection
PolicyGDPR
Right to be Forgotten Right to UnderstandRight to be informed
(Hacked)Right to Data Protection
GDPR Structure in ASG Data Intelligence
Context Compliance GDPR Anti-Trust Sarbanes Oxley CCAR/KYC/BCBS 239 State International
DEMONSTRATION OF
DATA INTELLIGENCE
Q & ANEXT STEPS
THANK YOU