Holistics Overview
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The document discusses a comprehensive data transformation and reporting solution that enhances Amazon Redshift's capabilities. It highlights the features offered by Holistics, including data ingestion, scheduled transformations, SQL-friendly reporting, and powerful access control, aimed at streamlining data management and analytics for users. Key benefits include cost-effectiveness, ease of use for analysts, and improved efficiency in data presentation and interaction.
Holistics Overview
- 1. DATA TRANSFORMATION AND REPORTING FOR YOUR AMAZON REDSHIFT ▪ www.holistics.io
- 2. THE DISRUPTION OF AMAZON REDSHIFT Source: Amazon Redshift A fast and powerful, petabyte-scale data warehouse that is: A Lot Faster A Lot Cheaper A Lot Simpler Runs on SQL
- 3. TYPICAL REDSHIFT USE-CASE ▪ Data from production databases and other sources are imported into Amazon Redshift on an hourly/daily basis ▪ Data then gets aggregated, summarized, and derived inside Amazon Redshift ▪ The transformed data is then being analyzed, explored and presented to business users through some internal web interfaces. TRANSFORM USER 1 USER 2 USER 3 Event Based Data Third Party APIs Production DBs IMPORT PRESENT
- 4. CHALLENGES FOR REDSHIFT USERS Data Import ▪ Write script to load data into Redshift (split data, upload into S3, load into tables) ▪ Manually manage & performance-tune Redshift tables (sortkeys, distkey, compression types) Data Transformation: ▪ Write scripts to create aggregated/summarized tables from existing tables ▪ Manage the scheduling of the tasks Data Extraction: ▪ Spend time building web interface front-end to present data ▪ Spend time extracting and emailing data to users TRANSFORM USER 1 USER 2 USER 3 Event Based Data Third Party APIs Production DBs IMPORT PRESENT
- 5. THE HOLISTICS APPROACH HOLISTICS DATA PRESENTATION AND EXPLORATION Access Control Report Filters Audit Trails Report Charts Report Dashboards Pivot Table HOLISTICS REDSHIFT IN-MEMORY DATA TRANSFORMATION Aggregation Materialization HOLISTICS DATA INGESTION (Source Data) Import Production Databases Import Spreadsheet from Users Import Transform Present Report Creation Scheduled Emails Annotations An end-to-end UI on top of Amazon Redshift to manage your entire data pipeline process. Summarization Icon made by Freepik from www.flaticon.com
- 6. FEATURES HIGHLIGHTS ▪ Imports: ▪ Loading of production databases (PostgreSQL) into Redshift ▪ Uploading of user-generated data (CSV, Excel) into Redshift ▪ Manage & Transformations: ▪ Scheduled transformations within Redshift ▪ Manage Redshift tables with simple UI ▪ Reporting & Presentation: ▪ SQL-friendly reports & dashboards, KPI reporting ▪ Annotations ▪ Self-serving Pivot Table ▪ Automated report emails ▪ Powerful Access Control Management
- 7. FEATURES – BY ROLE ▪ Analysts & Admins: ▪ Flexible report creations: Create reports, charts and dashboards for business users (using SQL) ▪ Data transformations: create and manage scheduled aggregations within Redshift ▪ Business Users: ▪ View Reports: Browse and view reports ▪ Schedule report emails: receive regular report updates via emails ▪ Custom Data Uploads: Get custom data (Excel, CSV) into Redshift ▪ Pivot Table: Explore and interact with prepared data-sets
- 8. HIGHLIGHTS & BENEFITS 1. Focus on your core activities 2. Runs on SQL 3. Powerful Data Access Control 4. Fully Utilize Power of Amazon Redshift 5. Cost-effective
- 9. FOCUS ON YOUR CORE ACTIVITIES ▪ Engineers working on core product development instead of peripheral reporting tools ▪ Analysts spend more time providing new insights into data, and less time on manual repetitive information requests from users. ▪ Business users spend less time waiting for information and more time exploring what they need.
- 10. RUNS ON SQL ▪For Report Creation ▪ Friendly for novice SQL analysts to create simple reports ▪ Flexible for power SQL analysts to create complex reports ▪ Easy to hire and train new analysts ▪Extended syntax to complement SQL ▪ Report Filters ▪ Advanced data access control
- 11. FLEXIBLE AND POWERFUL DATA ACCESS CONTROL ▪Works well for any combination of user group permissions ▪Assign up to 5 levels of data access control ▪ Data Source Level ▪ User Level ▪ User Group Level ▪ Column Level ▪ Row Level
- 12. GET MORE OUT OF REDSHIFT ▪ Cost-saving: Direct your investment into Redshift to get you the highest performance per dollar for your analytics infrastructure ▪ Maximize resources utilizations: Fully leverage on the in-memory processing power of Redshift to run your data transformation and queries activities ▪ Simple UI: User interface to help simplify management of your data pipeline activities with Redshift ▪ No need to move your data outside of Redshift
- 13. COST-EFFECTIVE ▪ Computing resources costs for your BI tool (CPU, Memory) ▪ Cost of storage in your BI tool for data that is already in Redshift ▪ Cost of training and hiring for specific BI skill-sets
Editor's Notes
- #3: In February 2013, Amazon launched Amazon Redshift, a fast, cheap and fully-managed data warehouse that makes it simple and cost-effect to store and analyze all your data with existing business intelligence tools. Since then, the its growth has been phenomenal, companies have been on-boarding Amazon Redshift into their data platforms. Companies (especially technology startups) now can have a data-warehouse of their own for less than US$1000/TB/year
- #6: Icon made by Freepik from www.flaticon.com