DATAWATCH FEDERAL GOVERNMENT. Daniel Bolon, Account Manager Federal Programs Geoff Holm, Solutions Architect Federal Programs

Transcription

1 DATAWATCH FEDERAL GOVERNMENT Daniel Bolon, Account Manager Federal Programs Geoff Holm, Solutions Architect Federal Programs

2 Current FED Customers 2

3 40,000 Customers Worldwide Financial Services Healthcare Retail Other Industries 3

4 Data Preparation with Monarch Parsing PDF, Text to Data Sort, Filter, Calculations Transform Data - Pivot, Unpivot, Aggregate ACCESS MANIPULATE 3 ENRICH COMBINE LOAD Cleanse Individual Fields Merge with External Data Repeatable Process Downstream analytics Reporting 4

5 Datawatch Platform Acquire & Prepare Automation Service Content Repository Report Mining Monarch Swarm EXPORT TO VISUALIZATION TOOLS 5 May 19, 2017

6 Classic Request to Analyst from Senior Management I m considering reorganizing the teams to improve performance and I need you to look into historical results. Historical View of results By City By County By State By Team assigned Review Segmentation by: City / State Age / Education level Last 24 months Recourse Cost By City By County By State By Team assigned Review Resource Allocation Are Teams / Individuals effective and productive? Are expenses in line with policy? Can we correlate resources to results? It s Monday, I need it by Friday I m going to be unavailable for questions Make sure its accurate / its going to Sr Mgt Once I get it, I ll probably have more ideas 6

7 Wasted time preparing data Analysts waste up to 80% of their time preparing data versus analyzing $22,000 per year, per analyst wasted Blue Hill Research, March

8 Self-Service Data Prep for Federal Finance Professionals Access and prepare financial data from ANY source (static reports, database, core systems, web, etc.). Intuitively build repeatable workflows for ALL your financial management tasks like audit and reconciliation. Automatically parse financial data from PDF, text or multi-structured and report-based files from internal financial systems into rows and columns. Eliminate cumbersome VLOOKUPs and MACROs in Excel. Ensure data governance through data lineage logs and change histories. Socialize governed, certified, curated and raw data sets that can be shared by teams to enhance trust in data and improve productivity. STOP! Missed deadlines Inaccurate Incomplete Costly For use cases in: Accounting & Audit Compliance Reconciliation Financial Planning Budgeting Analysis Data Preparation for Visualization Acquisition Management Data Consolidation/Migration Labor Distribution Resource Management START! Experiencing Self-Service Data Prep 8

9 Monarch for Maintenance and Logistics Analysis Scrape data from web-based DoD portals like LOGSA, JOPES, SDDC, etc. and extract multi-structured data from system generated reports (SAMS-E/ULLS-A, IMDS, MSAT, TAMIS, PBUSE). Easily perform complex forecasting models for all classes of supply (ammunition, fuel, spare parts). Easily track service schedules, unscheduled maintenance and parts status all in one consolidated view. Drag-and-drop data preparation for visual Maritime Domain Analysis to know what assets are available, when and where. Perform quick, ad-hoc views and calculations of your data using point/click data transformations to eliminate reliability on manual Excel and PowerPoint updating. Understand how property transfers and/or acquisitions will affect hand-receipts and total value of financial responsibility. Organizations & End-Users: -USAF (AMC/AFMC) -Army (AMC) -NAVY (NAVSUP) -Marines (LOGCOM) -Joint (TRANSCOM/J4/J8) -Defense Logistics Agency -Maintenance Manager -Logistics Manager -Program Analyst -Systems Analyst -Mobility Officer -Ammunition Officer 9

10 Edwards Air Force Base Success Story OVERVIEW Needed to consolidate data from 7 different databases to ensure all pilots and planes were mission-ready. Different reports contained disparate information on training, crew member qualifications, maintenance records, etc. CHALLENGES Time and Accuracy th MXG was printing reports and manually rekeying all relevant information. SOLUTION Now automatically extract, manipulate and summarize data from plain text, PRN, ASCII, ANSI, PDF, XML, HTML and output to Microsoft XPS Can now spot critical trends across multiple databases RESULTS Introducing Monarch eliminated the 412 th MXG s database roadblock and expedited their reporting process from hours to 30 seconds Created more than 200 models to be automated, improved efficiency and informed decision-making throughout the organization 10

11 Data Prep for the Intelligence Community Enables analysts to spend more time analyzing data and less time finding and preparing data. Solve challenges with data overload, dark data, disparate data & intelligence sharing. Monarch Swarm is the industry s first data socialization tool designed for collaborative analytics with gamification Access more data, faster via automated PDF & TXT data extraction & transformation. Speed up time-to-analysis, eliminate repetitive tasks & duplication of effort by sharing pre-built models. Agnostic to any data source (Excel, PDF, TXT, CSV, HTML, JSON, XML, log files, etc.). Enrich data via web-scraping from websites, social media, etc. Automate distribution of curated data sets to teams, databases & warehouses. 3 Use Cases & End-Users: Intel Analysts Data Scientists Cyber Security Cloudera, Hadoop & other database admin/end-users Threat detection Pattern of life Forensic analysis Suspicious activity reports Data preparation for visualization/analytics 11

12 Turn HR processes into People Analytics Eliminate manual re-keying of data from clunky 3 rd party & internal system-generated reports. AHRS, COPS, DCPAS, DCPDS, DPRIS, DJMS, DQRY, EDAS, emilpo, iperms, IPPS-A, IWRS, MedPros, MyPers, PeopleSoft, TOPMIS, etc. Ease the burden on report creation with pre-built transformations, for automated deduping and reconciliation. Establish data governance and adhere to reporting standards using pre-built models. Improved confidence in accuracy of reporting decreases potential for incurring fines or penalties. Redact and/or mask sensitive data in reporting. Perform quick, ad-hoc reporting using filtering across any data values. Use Cases & End-Users: Army Navy Air Force Marines OPM DHS Organization Reporting: Payroll, Headcounts, promotions, termination & IT system access reconciliation, workforce planning & analytics, age band reporting Individual Reporting: Baselines, Orders, Deployment Readiness, training documents, Manpower analytics ERB/ORB, LES, OER, awards & decorations 12

13 Self-Service Data Prep for Government Recruiting Reconcile outreach lists with one another to make sure data is accurate, and easily de-duplicate names and numbers. Extract data from numerous web-based recruiting systems or databases. Build reports or summaries for leadership and automatically distribute and share with teams for analysis. Mitigate version control issues with multiple versions of similar data sets. Save hours daily updating data and doing the same tasks over and over. Web-scrape data from government or education websites, and easily extract Social Media data. For users in: DoD / Guard & Reserve / Intel Community Department of Homeland Security Under Secretary for Personnel & Readiness Defense Manpower Data Center JAMRS Program Accessions analysis and tracking Career Exploration Constantly wasting time in Excel or other systems? Waiting on IT or someone else for help? Manually entering data from reports, web pages, etc.? 13

14 Scale & Automate Workflows Archive Visual Analytics (Tableau, Qlik.) Export to SQL Input could also be a connection string to a database, website, etc. report distribution USAF Maintenance Report *Schedule processes by date/time or in a monitored fashion *Distribute data and reports directly into databases or via (integrates w/ active directory) Apply a model built in Monarch to transform your data the way you need *Update data marts or data warehouses *Notify when new data is available *Mask certain sensitive information as appropriate *Provide full audit history behind the data manipulation process Datawatch accepts any data types Data is now analytics ready *Segment distribution by individuals or groups 14

15 The Datawatch Difference ACQUIRE PREPARE AUTOMATE GOVERN SOCIALIZE CONSUME Access and extract virtually any data source or type: structured and semi/multistructured Intelligent UI with powerful engine Proven scalability to thousands of users Remove risk of non-managed data & processes Share, Collaborate, Like, Rate, Steward Analytics, Operational Processes, Data Mining, BI, Viz, Dashboards, etc 15 May 19, 2017