He has led many Bal solution deliveries in the domain of banking, financial arrives and telecommunications, which Include Enterprise Data Warehouse Annihilates for ICC Bank, Reserve Bank of India and British Telecommunications. He holds Bachelor of Technology degree In Electrical Engineering from IT Bombay. 2 Table of Contents Introduction 4 2. 3. Bal Technology Advancements 5 4. Conclusion 7 3 For more than two decades, organizations have been leveraging Business Intelligence (81) platforms with the sole objective of 'management by facts' for business benefits.

Traditionally, Bal platforms have been spanning across Information Integration (e. G. TTL, EAI/ESP.., CDC), Information Storage (e. . Data Warehouse, Cubes, Metadata) and Information Analytics (e. G. Enterprise Reports, OLAP Reports, Dashboards and Data Mining) components. Over this period, the landscape of Bal has changed with the touch of business integration and innovation. And this change is not Just limited to the corporate world.

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The police force using advanced Bal to bring down the crime rate with an agile work force, military operations using predictive analytics to move troops for desired results and GIs-based Tsunami early warning systems, are a few live examples of how Bal systems have matured to benefit the humanity. Bal is definitely one of the most important business initiatives, which has shown a positive impact on the health of organizations. A lot of questions are raised regarding the definition and the scope of the Bal platform to get clarity on the maturity of the Bal initiative and the technology backbone to yield business benefits.

After getting the desired benefits from the Bal initiative, the usual question has been "What next? ". Bal Solution Paradigm In the current dynamic market, the rate of change is faster than yesterday and what we do today may not be relevant tomorrow. E. G. Change in the landlines tariff didn't append for more than a decade, but mobile tariff and service plans are changing on an almost quarterly basis. To survive and grow in the vibrant market space, every organization is facing outrageous competition, business convergence, demand for profitable growth and intense pressure on cost.

Organizations are becoming innovative in their approach to make business truly performance driven at Strategic, Tactical as well as Operational levels. The frame of reference is in which an e. G. Relationships with customers, suppliers, partners, employees, regulatory authorities and sub-contractors. With precise behavioral analysis, prediction and correlation of the relationship, appropriate action can be taken at the right point in time through 81; otherwise the cost of managing the relationships can escalate and business could also suffer.

E. G. Without fully understanding the customer profile (demographic, cryptographic and socioeconomic) and portfolio, if an add-on offer is made through cold calls, the cost will be higher and so will the chance of dissatisfaction, resulting in customer churn. For business excellence, innovation is necessary and there is no innovation without risk. Hence for better performance, it is necessary to minimize the area outside the area under control I. E. The Risk Area. Precision in predicting risk (e. G. Reedit risk, market risk, operational risk) with Bal provides the advantage of having more Capital available for operations as well as innovation e. G. Regulatory Authorities relax the Cash Reserve requirement, if predictions in Risk Management are consistently well under the threshold. Risk Area Relationship Frame Performance Area (Area under Control) Management Risk Relationship Optimization The Journey towards business excellence is facilitated by the Pervasive Bal correlating he Performance Management, Relationship Optimization and Risk Management at all levels in the organization.

Hence similar to business excellence, BI is a Journey and not a destination. Along with traditional tools and technologies (I. E. TTL, OLAP, Appliances, Dashboards, Mining), new technologies have started finding their place under the Bal umbrella due Value Lost Focus on operational efficiency: The philosophy is to have the right information available to the right person at the right time'. As per the Time-Value Curve for Decision Making, business value decays with time and the definition of the 'right time' upends purely on the optimization need in the business decision making cycle.

If a call center person needs to perform the 'Best Action' while interacting with the customer, Value Growth in Data volume: Globalization, consolidation and increase in customer and product base have resulted in tremendous growth in data volume. This has led to the increased use of appliances, and data compression. Since data usage patterns are different for data created during different periods, it's not necessary to use all of the computing power (powerful disks, memory and processors) for the whole dataset in a data warehouse.

Critical or important datasets can be given main computing power, while keeping the other datasets (mostly >70% of whole dataset) in inactive (not necessarily offline) state with the help of ELM (Information Lifestyle Management) products. This significantly increases system performance with the same computing power. Business Event Data ready for Analysis Information Delivered Capture Latency Analytics Action Time Action Taken Time he/she needs to know the as-of-now customer profile (e. G. Customer information along multiple focus areas such as Account / Subscription, Affinity towards Products,

Campaigns sent and Faults reported). In the absence of that, improper action may be taken resulting in customer churn. In this case, the as-font information can be with 5-10 minutes latency. But when it comes to surveillance at a Stock Exchange, the responses need to be on near-real time basis. This need has brought EAI/ESP.. (l middleware), Ell (Enterprise Information Integration), CDC and BAM (Business Activity Monitoring) tools into the picture for decision making on near-real time basis.

The next level of decision making in the operational space has been greatly enabled by Rules Engines e. G. Determining 'Next Best Action' to control customer churn at call centers and CAPE (Complex Event Processing) products e. G. Algorithmic Trades in Capital Markets, predicting right price in the Commodity Exchange trades. CAPE has been in use in the military and capital market for more than a decade. Just a couple of years ago, it has entered the commercial market for requirements such as enriching end customer experience, fault identification, price prediction and fraud detection.

In order to satisfy system performance with simultaneous READ / WRITE operations needed for near-real time decision making, the demand for handling of axed workload in databases has increased. This is bringing in-memory databases and solid-state drives onto the scene. Advanced information delivery: There is a significant change in data visualization techniques for better understanding of data. GIS or integration with maps (e. G. Google maps) has improved the productivity of decision makers e. G. Analysis of telecoms products and services in a locality along with penetration of competitor products. Flash-based reports and dashboards have increased the richness of user experience. Faster information delivery through products using in-memory features also finds better acceptance. There is also an increase in the information delivery channels. Mobiles and tablets have increased the mobility of stakeholders and hence alerts, dashboards and quick tips are available to sales force, managers and executives on these devices.

Even campaign distribution to shortlist consumers is happening through such channels. Content Analytics: Textual information stacked up in organizations is being put to good use due to advancements in Text/Content Mining. Text mining algorithms, to find trends in product service claims and alter the design to reduce the warranty cost, to find patterns of irregularity (black-spots) in telecoms network elements and proactively fix them to reduce downtime, have changed the way organizations have been looking at their content.

Even to improve call center efficiency, voice data is processed through speech synthesis software and patterns, such as fast issue resolution, standard product issues, and standard operating procedures, which are Internet. Sentiment analysis, topic analysis, opinion tracking of products and services is possible. E. G. Film distributors planning movie promos at regular intervals, COP manufacturers changing packaging based on opinion tracking, news analysis to understand the impact of all possible events in the specific region on a specific product or service.

Importance of data quality: Failure to maintain the quality of data passing through an audit can cause a heavy penalty. Not understanding the unique customer/household may result in escalated cost and incorrect perception about the customer and portfolio. 'Garbage in - garbage out' philosophy has been taken very seriously by organizations and hence there is more adoption of data profiling, data laity, 6 data cleansing and master data management products.

Also if there is a failure to define centralized metadata, 'On Time Delivery may mean delivery against customer requested date for one unit and against promised date for another unit. Metadata management products are also gaining more acceptance in the market. But there is still the major issue of version control and automation in metadata inferences due to which metadata management products are not so widely used in the market. Lower TCO (Total Cost of Ownership): Eventually, the TCO plays a major role in the acceptance of technology products for an organization.

Pressure on reduction of the TCO has lead to adoption of platform vendors (e. G. MM, Oracle, SAP, Microsoft) instead of best-of-breed, Open Source (e. G. Hoodoo, Jasper, Pentane) and solution hosting (on cloud, hosted environment). In spite of availability of advanced Bal technologies in the market, most companies are still struggling to get the Bal foundation right I. E. To set up an Enterprise Data Warehouse and governance and get reports and dashboards. Once the right foundation is set for 81, adoption of the new technologies and the path towards unconstitutionality of innovation can be laid out.